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AI Strategy, Governance, and Data Analysis for Managers

University of Michigan via Coursera Specialization

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 10 hours a week
Sessions

Self-Paced
Level

Beginner

Found in

Overview

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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.

Syllabus

Course 1: Generative AI Essentials: Overview and Impact
Course 2: AI-Powered Data Analysis: A Practical Introduction
Course 3: Generative AI: Governance, Policy, and Emerging Regulation

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With the rise of generative artificial intelligence, there has been a growing demand to explore how to use these powerful tools not only in our work but also in our day-to-day lives. Generative AI Essentials: Overview and Impact introduces learners to large language models and generative AI tools, like ChatGPT. In this course, you’ll explore generative AI essentials, how to ethically use artificial intelligence, its implications for authorship, and what regulations for generative AI could look like. This course brings together University of Michigan experts on communication technology, the economy, artificial intelligence, natural language processing, architecture, and law to discuss the impacts of generative AI on our current society and its implications for the future. This course is licensed CC BY-SA 4.0 with the exclusion of the course image.
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In “Generative AI: Governance, Policy, and Emerging Regulation,” you’ll discuss governance considerations for generative artificial intelligence (AI) systems deployed in an organization and explore data management practices, transparency methods, risk and impact assessments, and management approaches that ensure generative AI is developed and deployed responsibly. The course also provides an overview of the current generative AI policy and regulatory landscapes within the United States, European Union, and G7 countries. By exploring governance issues and the current regulatory landscape regarding AI, you’ll gain a deeper understanding of how to integrate, manage, and monitor AI within your organization.
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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. Learn how to navigate this new terrain, whether you're a complete novice or looking to enhance your skills. 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 platform. 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. This is the first course in the Applied AI: Data Analysis, Workflows, and Decisions series, a three-course series on practical ways to integrate AI into your personal and professional routines.