5 Learning Experiences
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In "AI Strategy, Governance, and Data Analysis for Managers," you’ll build practical generative AI skills for management, data analysis, and responsible organizational use. You’ll learn how generative AI and large language models work, where tools such as ChatGPT can add value, and how to weigh benefits, drawbacks, authorship, ethics, and social impact.
You’ll then apply generative AI to data analysis by developing analysis ideas, asking effective questions, generating functional code, visualizing data, and avoiding common mistakes. You’ll also prepare a Python environment and datasets that can support continued practice and optional sharing on GitHub. For organizational decision-making, you’ll examine data management, transparency, risk and impact assessments, stakeholder needs, costs, governance expectations, and emerging AI policy and regulation in the United States, European Union, and G7. Across the course series, you’ll practice applying generative AI to realistic management and analysis decisions.
This course series is designed for managers and professionals who want to evaluate, use, and govern generative AI with stronger judgment.
5 Learning Experiences
Data Science Ethics Lecturer, School of Information
4 Learning Experiences
Assistant Professor of Anthropology and Assistant Professor of Ecology and Evolutionary Biology
3 Learning Experiences
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Explore generative AI essentials, ethical use, authorship, and regulation through expert insights on AI’s impact on society and work.
Learn to use AI tools like ChatGPT to analyze, visualize, and interpret data for real-world applications and projects.
Explore governance strategies and global regulatory frameworks to ensure generative AI is deployed ethically and transparently in organizations.