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DTSTART;TZID=Europe/Helsinki:20260920T080000
DTEND;TZID=Europe/Helsinki:20260924T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043117-1789891200-1790269200@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *Address		\n			Participants Address Email\n			\n		\n		Address Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2026-09-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20261020T080000
DTEND;TZID=Europe/Helsinki:20261024T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043118-1792483200-1792861200@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLast		\n			Name Address 3\n			\n		\n		Email *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2026-10-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20261120T080000
DTEND;TZID=Europe/Helsinki:20261124T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10030975-1795161600-1795539600@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *Address		\n			Email Name Course\n			\n		\n		Address Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2026-11-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20261220T080000
DTEND;TZID=Europe/Helsinki:20261224T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043119-1797753600-1798131600@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participants		\n			Number of Contact\n			\n		\n		Additional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2026-12-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270120T080000
DTEND;TZID=Europe/Helsinki:20270124T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043120-1800432000-1800810000@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participants		\n			organization Address Venue\n			\n		\n		Additional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-01-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270220T080000
DTEND;TZID=Europe/Helsinki:20270224T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043121-1803110400-1803488400@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional Information		\n			Address of Name\n			\n		\n		Organization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-02-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270320T080000
DTEND;TZID=Europe/Helsinki:20270324T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043122-1805529600-1805907600@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participants		\n			Course Type Line\n			\n		\n		Additional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-03-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270420T080000
DTEND;TZID=Europe/Helsinki:20270424T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043123-1808208000-1808586000@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLast		\n			Organization details Line\n			\n		\n		Organization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-04-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270520T080000
DTEND;TZID=Europe/Helsinki:20270524T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043124-1810800000-1811178000@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *		\n			Participants 3 of\n			\n		\n		AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-05-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270620T080000
DTEND;TZID=Europe/Helsinki:20270624T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043125-1813478400-1813856400@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *		\n			organization Course details\n			\n		\n		Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-06-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270720T080000
DTEND;TZID=Europe/Helsinki:20270724T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043126-1816070400-1816448400@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *		\n			Address Course Email\n			\n		\n		Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-07-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270820T080000
DTEND;TZID=Europe/Helsinki:20270824T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10030984-1818748800-1819126800@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *		\n			Participants Organization Number\n			\n		\n		Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-08-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20270920T080000
DTEND;TZID=Europe/Helsinki:20270924T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043127-1821427200-1821805200@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLast		\n			Participants Course Organization\n			\n		\n		Organization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-09-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20271020T080000
DTEND;TZID=Europe/Helsinki:20271024T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043128-1824019200-1824397200@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubai		\n			Participants Details Course\n			\n		\n		Additional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-10-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20271120T080000
DTEND;TZID=Europe/Helsinki:20271124T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043129-1826697600-1827075600@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubai		\n			Phone Contact Address\n			\n		\n		Additional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-11-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20271220T080000
DTEND;TZID=Europe/Helsinki:20271224T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043130-1829289600-1829667600@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participants		\n			Line Contact of\n			\n		\n		Additional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2027-12-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280120T080000
DTEND;TZID=Europe/Helsinki:20280124T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043131-1831968000-1832346000@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)		\n			Additional of Email\n			\n		\n		Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-01-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280220T080000
DTEND;TZID=Europe/Helsinki:20280224T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043132-1834646400-1835024400@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.		\n			Number Course of\n			\n		\n		Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-02-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280320T080000
DTEND;TZID=Europe/Helsinki:20280324T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043133-1837152000-1837530000@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)		\n			of Organization from\n			\n		\n		Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-03-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280420T080000
DTEND;TZID=Europe/Helsinki:20280424T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043134-1839830400-1840208400@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubai		\n			Additional Details 2\n			\n		\n		Additional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-04-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280520T080000
DTEND;TZID=Europe/Helsinki:20280524T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043135-1842422400-1842800400@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLast		\n			Number Name Venue\n			\n		\n		Organization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-05-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280620T080000
DTEND;TZID=Europe/Helsinki:20280624T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043136-1845100800-1845478800@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *		\n			from Course organization\n			\n		\n		AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-06-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280720T080000
DTEND;TZID=Europe/Helsinki:20280724T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043137-1847692800-1848070800@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)		\n			Address Participants Address\n			\n		\n		Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-07-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280820T080000
DTEND;TZID=Europe/Helsinki:20280824T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043138-1850371200-1850749200@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *		\n			Participants Line Name\n			\n		\n		Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-08-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20280920T080000
DTEND;TZID=Europe/Helsinki:20280924T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043139-1853049600-1853427600@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLast		\n			Applicant Email Additional\n			\n		\n		Email *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-09-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20281020T080000
DTEND;TZID=Europe/Helsinki:20281024T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10030998-1855641600-1856019600@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLast		\n			Address Additional 2\n			\n		\n		Organization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-10-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20281120T080000
DTEND;TZID=Europe/Helsinki:20281124T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043140-1858320000-1858698000@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm Email		\n			Course Organization Number\n			\n		\n		Phone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-11-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20281220T080000
DTEND;TZID=Europe/Helsinki:20281224T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043141-1860912000-1861290000@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLast		\n			Address Details Name\n			\n		\n		Address Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2028-12-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20290120T080000
DTEND;TZID=Europe/Helsinki:20290124T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043142-1863590400-1863968400@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *Address		\n			Address Information Phone\n			\n		\n		Address Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2029-01-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
ATTACH;FMTTYPE=image/jpeg:https://basatraining.com/wp-content/uploads/2025/01/dfghhh-2kFwYO-1.jpg
ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20290220T080000
DTEND;TZID=Europe/Helsinki:20290224T170000
DTSTAMP:20260202T090809Z
CREATED:20250114T220000Z
LAST-MODIFIED:20260202T090809Z
UID:10043143-1866268800-1866646800@basatraining.com
SUMMARY:DATA ANALYTICS AND ARTIFICIAL  INTELLIGENCE
DESCRIPTION:DATA ANALYTICS AND ARTIFICIAL INTELLIGENCE\nOVERVIEW\nThe richest data store is only as good as your ability to search\, sort\, analyze\, and present the data within it. This introductory-level course will give participants a broad overview of the theory and practice of data analytics and the many ways in which artificial intelligence (AI) contributes to it. \nIt will begin with a brief history of data analytics and then proceed into discussions of data warehouses\, data mining\, business intelligence\, machine learning\, and other emerging AI techniques to make sense of big data. \nParticipants will learn how data is captured\, cleansed\, analyzed\, and presented on business intelligence dashboards that captivate and persuade an audience. \n“It is a capital mistake to theorize before one has data\,” Sherlock Holmes once said. Whether you are investigating analytics as a potential career move or wish to better understand the terminology you encounter with increasing frequency in your professional circles\, this course will give you the foundation you are looking for. \nWHAT YOU WILL LEARN:\n\nA brief overview of the history of analyzing data\, from medieval statistics to the sophisticated techniques developed by the likes of Google and Microsoft.\nA look at data stores\, which are growing exponentially\, and the challenges of wrangling “big data.”\nUnderstanding of data mining—what it entails\, different approaches\, and who’s leading the way.\nA two-part discussion of business intelligence\, including the principles of sound dashboard design and data presentation.\nThe key differences between the four types of analytics— diagnostic\, descriptive\, predictive\, and prescriptive\nAn overview of specific analytics processes and models.\nA first look at AI\, its evolution\, its functions\, and what it can do for businesses today.\nAn exploration of machine learning—how systems can learn from data\, identify patterns\, and make decisions with little human intervention.\nA survey of deep learning technologies\, including a variety of neural networks.\nAn overview of the most important machine learning data modeling techniques\nA practical and honest appraisal of the analytics and AI landscape today and moving forward\, including the tremendous promise and the potential pitfalls.\nResources for continued study on these topics.\n\nWHO SHOULD ATTEND?\n\nPeople who want to start their careers in data analytics\nThose who want to learn the basic concepts of data analytics and AI\nIndividuals who want to kickstart their data science skills\n\nOutline\n\n\nFoundations of Data Analytics\n\n\n\nThe evolution of data analytics: from early statistics to modern data science\nKey concepts: data\, information\, insight\, knowledge\nThe role of analytics in digital transformation\nOverview of data types (structured\, semi-structured\, unstructured)\nThe anatomy of a data-driven organization\n\n\n\nData Management\, Cleaning & Preparation\n\n\n\nThe data lifecycle: collection\, storage\, and management\nData warehouses vs. data lakes\nChallenges of big data (volume\, velocity\, variety\, veracity\, value)\nData wrangling and cleaning techniques\nTools overview: Excel\, Power Query\, Python basics\n\n\n\nDay 3: Business Intelligence & Data Visualization\n\n\n\nWhat is Business Intelligence (BI)?\nTransforming data into insights\nDashboard design principles and storytelling with data\nOverview of BI tools: Power BI\, Tableau\, Google Data Studio\nKey performance indicators (KPIs) and performance dashboards\n\n\n\n\n\n\n\nDay 4: Introduction to Artificial Intelligence & Machine Learning\n\n\n\nWhat is Artificial Intelligence (AI)? Definitions and real-world applications\nKey differences between AI\, Machine Learning (ML)\, and Deep Learning\nHow machines learn from data: supervised\, unsupervised\, and reinforcement learning\nExamples of AI in action: chatbots\, recommendation systems\, predictive analytics\nOverview of popular ML algorithms (decision trees\, regression\, clustering)\n\n\n\nDay 5: The Future of Analytics & AI Integration\n\n\n\nThe four types of analytics: descriptive\, diagnostic\, predictive\, prescriptive\nEmerging AI technologies: natural language processing\, computer vision\, and generative AI\nBuilding a data-driven culture in organizations\nOpportunities\, risks\, and ethical implications of AI\nContinuing learning pathways and certifications in data analytics & AI\n\n\n\n\n\nEvent Coordinated by BASA Training \nYou can also visit our Online Courses Website Excel Elearning \nYou can also get an affordable ebook on ebooksnest.com \n\n\n\n\nRegistration Form\nPlease enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form.Applicant Details *FirstLastEmail *EmailConfirm EmailPhone Number *Course Type *--- Select Choice ---CertificationsAccounting and FinanceAdministrationAuditing and GovernanceBankingBusiness Continuity and Crisis ManagementCommunication and Writing SkillsConferenceCustomer ServiceData Analytics and Artificial IntelligenceData Management and Business IntelligenceDigital Innovation and TransformationGovernment and Public SectorHuman Resources and TrainingInsurance and Financial ServicesInterpersonal Skills and Self DevelopmentIT Management and Cyber SecurityLeadership and ManagementManagementPlanning and Strategy ManagementProject ManagementPublic RelationsQuality and ProductivityRisk and ComplianceSafety and EnvironmentSecurity ManagementSelect the correct course category (typically found below in the course details)		\n			Type Contact Email\n			\n		\n		Course Name *Course VenuePretoria\, South AfricaDurban\, South AfricaCape Town\, South AfricaKigali\, RwandaHarare\, ZimbabweDubaiAdditional InformationOrganization Name *AddressAddress Line 2 *FirstLastAddress Line 3 *FirstLastOrganization Contact DetailsFirstLastNumber of Participants from organization\n\n\n\n	Participants: 1\nUse the slider to chose whether you want to register only 1 or 10 participantsAdditional Participants detailsSubmit
URL:https://basatraining.com/course/data-analytics-and-artificial-intelligence-2-2/2029-02-20/
LOCATION:Pretoria\, 484 Hilda St\, Hatfield\, Pretoria\, Gauteng\, 0083\, South Africa
CATEGORIES:Data Management and Business Intelligence,IT Management and Cyber Security
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ORGANIZER;CN="BASA":MAILTO:info@basatraining.com
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