Applied AI: Data Analysis, Workflows, and Decisions

University of Michigan via Coursera Specialization

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Overview

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AI is quickly turning into a powerful tool for analyzing information, improving productivity, and supporting decision-making. But knowing how to use it effectively goes beyond basic prompting skills. In Applied AI: Data Analysis, Workflows, and Decisions, you’ll learn how to work with AI to solve problems, streamline processes, and make better decisions. Through hands-on projects and practical frameworks, you’ll explore how to analyze data with AI, find opportunities to automate routine work, improve workflows, and evaluate complex choices. You'll also learn systems-thinking approaches that help you see connections, anticipate consequences, and design more effective ways of working. By the end of the Specialization, you’ll have created workflows that allow you to use AI as a collaborative force that supports your analysis, aids in problem-solving, and allows you to make decisions with confidence in your personal and professional life.

Syllabus

Course 1: AI-Powered Data Analysis: A Practical Introduction
Course 2: Systems Thinking for AI & Automation
Course 3: Rethink How You Decide with AI

Courses

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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.
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The right questions make AI a valuable tool for decision-making. "Rethink How You Decide with AI" teaches you how to use AI as a thought partner, allowing you to make more intentional, informed decisions. Through guided activities, reflection, and hands-on AI exploration, you'll examine the habits, assumptions, and patterns that shape your choices. You'll identify the constraints and tradeoffs behind real decisions, compare different approaches to setting priorities, and practice using AI to generate perspectives, challenge assumptions, and uncover blind spots. Your goal isn’t finding the "perfect answer," it’s developing a flexible decision-making process that evolves with you. Along the way, you'll learn how to use generative AI to stress-test ideas, evaluate alternatives, and strengthen your reasoning while maintaining ownership of your decisions. By the end of this course, you’ll have a personalized system that supports your decision-making, allowing you to move forward with your ideas with great clarity, confidence, and intention. This is the third 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.
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AI can help you work faster—but only when it's applied to the right problems. "In Systems Thinking for AI & Automation," you'll learn how to identify tasks worth automating, avoid common automation mistakes, and create workflows that save time and reduce manual effort. Through hands-on activities, you'll apply the IDEA framework—Identify, Document, Experiment, Adjust— a practical approach to making more thoughtful automation decisions. You'll explore the technologies behind modern automation, including no-code tools, low-code platforms, APIs, AI-assisted scripting, and generative AI. You'll also learn how to organize information and knowledge so AI tools can find, use, and build on it more effectively. Whether you're looking to streamline your work, improve team processes, or make better use of AI tools, this course will help you design practical, scalable tools that support productivity today and adapt to future advances in AI and automation. This is the second 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.