5 Learning Experiences
AI Strategy, Governance, and Data Analysis for Managers
3-Course Series
12 hours
4 hours per course (approx.)
About AI Strategy, Governance, and Data Analysis for Managers
In this Specialization, 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. This Specialization is designed for managers and professionals who want to evaluate, use, and govern generative AI with stronger judgment.
Applied Learning Project
Across the Specialization, you’ll practice applying generative AI to realistic management and analysis decisions. In the data analysis course, you’ll use generative AI to develop analysis ideas, generate functional analysis code, visualize data, and check for common mistakes. A final activity helps you prepare a Python environment and datasets for continued learning, with the option to showcase work on GitHub. In the governance course, you’ll apply responsible AI analysis to decisions involving data management, transparency, risk and impact assessments, stakeholders, costs, policy, and regulation. You’ll also evaluate the benefits, drawbacks, ethical use, authorship, and broader impact of generative AI through course activities and assessments.
Skills You'll Gain
- Data Ethics
- Brand Management
- Data Analysis
- Ethical AI
- Decision Making
- Artificial Intelligence
- Policy Analysis
- Generative Artificial Intelligence
- AI Innovation
- Generative Model Architectures
- Data Management
- Risk Management
- Responsible AI
- AI-Based Legal Compliance
- ChatGPT
- Problem Solving
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.
3 Courses in this series
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Free U-M Access CourseGenerative AI Essentials: Overview and Impact
Explore generative AI essentials, ethical use, authorship, and regulation through expert insights on AI’s impact on society and work.
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Free U-M Access CourseAI-Powered Data Analysis: A Practical Introduction
Learn to use AI tools like ChatGPT to analyze, visualize, and interpret data for real-world applications and projects.
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Free U-M Access CourseGenerative AI: Governance, Policy, and Emerging Regulation
Explore governance strategies and global regulatory frameworks to ensure generative AI is deployed ethically and transparently in organizations.
