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

- Module Introduction and Learning Objectives
- Video: Generative AI for Data Analytics
- Reading: Generative AI Tools for Data Analytics
- Video: Examples of Generative AI in Data Analytics
- Reading: Case Study on Successful Implementations of Generative AI in Data Analytics
- Lab: Explore a Simple Generative Tool
- Discussion Prompt: Discuss How Generative AI Can Be Used in Data Analytics
- Reading: Leveraging Generative AI in Data Analytics Process
- Demo Video: Generative AI for Data Generation and Augmentation
- Lab: Generative AI for Data Generation and Augmentation
- Demo Video: Generative AI for Data Preparation
- Lab: Generative AI for Data Preparation
- Demo Video: Generative AI for Querying Databases
- Lab: Generative AI for Querying Databases
- Video: Generative AI for Q and A Model Insights
- Lab: Generative AI for Q and A Model Insights
- Video: Successful Implementations of Generative AI for Data Preparation and Insights
- Reading: Using Microsoft Copilot
- Module 1 Practice Quiz: Data Analytics and Generative AI
- Module 1 Summary: Data Analytics and Generative AI
- Module 1 Cheat Sheet: Data Analytics and Generative AI
- Module 1 Graded Quiz: Data Analytics and Generative AI

Module 2: Use of Generative AI for Data Analytics

- Module Introduction and Learning Objectives
- Demo Video: Generative AI for Data Insights
- Lab: Generative AI for Data Insights
- Demo Video: Generative AI for Data Visualization
- Lab: Generative AI for Data Visualization
- Video: Generative AI for Creating Dashboards
- Lab: Generative AI for Creating Dashboards
- Video: Generative AI for Storytelling
- Lab: Generative AI for Storytelling
- Discussion Prompt: Dashboarding and Storytelling with Generative AI
- Video: Successful Implementations of Generative AI for Data Visualization and Storytelling
- Video: Considerations While Using Generative AI in Industries
- Video: Challenges While Using Generative AI
- Reading: Responsible Generative AI for Data Professionals
- Case Study: Considerations While Using Generative AI in Healthcare
- Lab: Considerations for Data Professionals Using Gen AI
- Module 2 Practice Quiz: Use of Generative AI for Data Analytics
- Module 2 Summary: Generative AI for Data Visualization and Storytelling
- Module 2 Cheat Sheet: Use of Generative AI for Data Analytics
- Module 2 Graded Quiz: Use of Generative AI for Data Analytics

Final Project and Exam

- Reading: Guided Practice Project Overview
- Lab: Guided Practice Project
- Final Exam

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

Mastering Generative AI for Data Analytics

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