Assistant Professor
AI-Powered Data Analysis: A Practical Introduction
What You'll Learn
- Learn principles of data analysis
- Learn how to use generative AI to come up with data analysis ideas
- Learn how to use generative AI to create functional data analysis code
- Learn how to share data analysis projects on GitHub
3 Modules
3 Hours
1 hr per module (approx.)
Rating
About AI-Powered Data Analysis: A Practical Introduction
As generative artificial intelligence (AI) reshapes our world, the ability to analyze data is quickly becoming as fundamental as reading and writing. “AI-Powered Data Analysis: A Practical Introduction” explores how AI tools like ChatGPT are revolutionizing our approach to data, making advanced analysis accessible to everyone. Whether you're a complete novice or looking to enhance your skills, you'll learn how to navigate this new terrain.
You'll learn to think critically about the context of data analysis, delve into the specifics of analyzing and visualizing data using AI, and consider broader factors that support but are not directly part of data analysis. This practical approach focuses on generative AI tools, ensuring you know how to ask the right questions to avoid common mistakes.
Your final activity will allow you to set yourself up for continued learning with a prepared Python environment and data sets, which you can voluntarily showcase on GitHub—a code-sharing hub. By the end of this course, you'll be adept at using AI tools to analyze data effectively and seamlessly apply these skills to future projects.
Skills You'll Gain
- AI Innovation
- ChatGPT
- Data Analysis
- Data Management
- Generative AI Agents
- Generative Artificial Intelligence
- Problem Solving
- Python For Data Analysis
What You'll Earn
- Certificate of Completion:
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Welcome Message
Welcome to AI-Powered Data Analysis: A Practical Introduction, a course designed to help learners use generative AI tools to support data analysis and problem-solving. Rather than teaching comprehensive analytics, the course emphasizes learning how to ask questions, retrieve information, customize solutions, and interpret results using AI as a learning partner.
This abbreviated syllabus description was created with the help of AI tools and reviewed by staff. The full syllabus is available to those who enroll in the course.
Course Schedule
Module 1: Laying the Groudnwork: Data Foundations
- Video: Welcome to Course
- Reading: How GenAI is Used in this Course
- Reading: Generative AI Options
- Reading: Course Syllabus
- Reading: Help Us Learn About You!
- Video: What Even is Data, Anyway?
- Video: Data Acquisition and GenAI
- Reading: Brainstorming and Searching with GenAI
- Video: Data: Contents & Containers
- Reading: Data Vocabulary
- Graded: Module 1 Quiz
Module 2: Building Skills: Essential Practice
- Video: What is Data Analysis?
- Video: Tool Diversity
- Video: Data Types and Structures
- Video: Data Wrangling
- Reading: Step 0 Context and Setup
- Reading: Data Wrangling Examples with GenAI
- Video: Data Analysis
- Reading: Data Analysis Examples with GenAI
- Video: Data Visualization
- Reading: Data Visualization Examples with GenAI
- Reading: Introduction to Jupyter Labs
- Ungraded Lab: Module 2 Lab
- Graded: Module 2 Quiz
Module 3: Finishing Touches: Supporting Skills & Next Steps
- Video: Supporting Skills
- Video: GenAI as Technical Assistant
- Reading: Create a GitHub Account
- Ungraded Lab: Module 3 Lab
- Reading: Post-Course Survey
- Reading: Continue your AI education with the AI Collection from Michigan Online
- Graded: Module 3 Quiz
Grading Policy
Learners must earn 80% overall to pass. There are three module quizzes, each worth approximately 33% of your final grade.
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Beginner Level
Basic familiarity with computers and internet search is recommended.
What Learners Are Saying
Imagine Generative AI as your on-demand data analytics consultant. You are still in charge... but AI makes sure you are never starting from a blank page.
Tina Lasisi Assistant Professor, Literature, Anthropology
