University of Michigan

Systems Thinking for AI & Automation

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University of Michigan

Systems Thinking for AI & Automation

Tina Lasisi

Instructor: Tina Lasisi

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Determine which workflows to automate and how, using proven assessment frameworks.

  • Explore different tools that support the automations you want to incorporate. 

  • Interpret and adapt AI-generated outputs for practical use in personal and professional life.

  • Design workflows that use quality data you provided to support scalable, AI-ready practices.

Details to know

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Recently updated!

June 2026

Assessments

3 assignments

Taught in English

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This course is part of the Applied AI: Data Analysis, Workflows, and Decisions Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

In this module, you will explore how to evaluate which tasks in your daily workflow are worth automating using a structured decision framework. You’ll assess potential time savings and reflect on where automation adds value, or carries hidden costs, so that you can choose the right tasks to optimize.

What's included

2 videos5 readings1 assignment1 discussion prompt

In this module, you will explore the landscape of automation tools, from no-code platforms to AI-assisted scripting, and understand how APIs enable systems to connect and communicate. Through a guided practice, you will learn to use GenAI tools to generate automation examples and evaluate them safely.

What's included

3 videos4 readings1 assignment1 discussion prompt

In this module, you will discover how structured information capture can serve as a powerful form of automation. Our goal is to rethink how you can store and retrieve knowledge by making your data AI-ready, low-friction, and semantically searchable.

What's included

1 video6 readings1 assignment1 discussion prompt

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Instructor

Tina Lasisi
University of Michigan
1 Course5,005 learners

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