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This Hands-on Masterclass on Data Analytics course offers an extensive overview of business analytics and machine learning, starting with the basics of data analytics to highlight its practical significance in the business world. The course delves into various types of business analytics, including descriptive, diagnostic, predictive, and prescriptive analytics. Participants will learn essential data fundamentals, including data types, sources, and common challenges such as format inconsistencies, missing data, and outliers, along with techniques for data cleaning, transformation, integration, and reduction. The course emphasizes the importance of data visualization, teaching best practices and tools such as Zero Code EDA, Tableau, Power BI, to effectively communicate insights. Participants will also gain a strong foundation in statistical methods, covering hypothesis testing, correlation and causation, and statistical tests like t-tests and chi-square tests. A significant portion of the course is dedicated to supervised and unsupervised machine learning. Participants will be introduced to key algorithms and techniques for regression, classification, clustering, and dimensionality reduction. The course leverages Zero Code tools to enable participants to apply machine learning models without coding, ensuring hands-on experience through practical exercises and case studies. In addition to technical skills, the course explores the latest trends in AI, including deep learning, neural networks, natural language processing, computer vision, and the ethical considerations of AI in big data.The course culminates in a comprehensive capstone project, where participants will apply their knowledge to a real-world scenario. They will collect and prepare data, select and implement models, evaluate and iterate their solutions, and present their findings in a final report. By the end of the course, participants will have a thorough understanding of analytics and machine learning concepts, reinforced through practical examples and tool usage, enabling them to apply these skills effectively in a business context.
Offered by Zero Code Learning50 hrsEnglishMr.Gaurav Gupta, Experience-25+ years, Qualification-Masters in Engineering., Mr.Vineet Srivastava, Experience-25+ years, Qualification-Bachelors in Engineering.
This Hands-on Masterclass on Data Analytics course offers an extensive overview of business analytics and machine learning, starting with the basics of data analytics to highlight its practical significance in the business world. The course delves into various types of business analytics, including descriptive, diagnostic, predictive, and prescriptive analytics. Participants will learn essential data fundamentals, including data types, sources, and common challenges such as format inconsistencies, missing data, and outliers, along with techniques for data cleaning, transformation, integration, and reduction. The course emphasizes the importance of data visualization, teaching best practices and tools such as Zero Code EDA, Tableau, Power BI, to effectively communicate insights. Participants will also gain a strong foundation in statistical methods, covering hypothesis testing, correlation and causation, and statistical tests like t-tests and chi-square tests. A significant portion of the course is dedicated to supervised and unsupervised machine learning. Participants will be introduced to key algorithms and techniques for regression, classification, clustering, and dimensionality reduction. The course leverages Zero Code tools to enable participants to apply machine learning models without coding, ensuring hands-on experience through practical exercises and case studies. In addition to technical skills, the course explores the latest trends in AI, including deep learning, neural networks, natural language processing, computer vision, and the ethical considerations of AI in big data.The course culminates in a comprehensive capstone project, where participants will apply their knowledge to a real-world scenario. They will collect and prepare data, select and implement models, evaluate and iterate their solutions, and present their findings in a final report. By the end of the course, participants will have a thorough understanding of analytics and machine learning concepts, reinforced through practical examples and tool usage, enabling them to apply these skills effectively in a business context.
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