Generative AI for Data Analytics demonstrates the integration of Generative Artificial Intelligence (Generative AI) in Data Analytics. This course demonstrates how to use generative AI tools/frameworks/platforms to increase the effectiveness of various processes involved in the data analytics life cycle.

You will learn how to use and apply generative models for tasks such as data generation, data augmentation, data preparation and finding insights, querying databases, generating visualizations, and storytelling. You will also explore challenges and ethical considerations associated with using Generative AI in data analytics.

Course Syllabus

Module 1: Data Analytics and Generative AI

Welcome
Data Analytics and Generative AI
Generative AI for Data Preparation and Insights
Module Summary & Assessment

Module 2: Use of Generative AI for Data Analytics

Generative AI for Data Visualization and Storytelling
Generative AI Considerations in Data Analytics
Module Summary & Assessment

Module 3: Final Project and Final Exam

Final Project
Final Exam
Course Wrap-Up

Course prerequisites:

An introductory knowledge of data analytics, generative AI, and prompt engineering would be beneficial. You can check these courses to get a basic understanding of these topics:

Learning Objectives

Describe how you can use Generative AI tools and techniques in the context of data analytics across industries
Implement various data analytic processes such as data preparation, analysis, visualization and storytelling using Generative AI tools
Evaluate real-world case studies showcasing the successful application of Generative AI in deriving meaningful insights
Analyze the ethical considerations and challenges associated with using Generative AI in data analytics

Generative AI: Enhance your Data Analytics Career

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