Systems Thinking for AI & Automation

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Systems Thinking for AI & Automation

This course is part of Applied AI: Data Analysis, Workflows, and Decisions Specialization

Instructor: Tina Lasisi

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3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

3 modules

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.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

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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.

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Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 3 modules in this course

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.

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

2 videosTotal 8 minutes

Weighing Automation Decisions4 minutes
The IDEA Framework4 minutes

5 readingsTotal 55 minutes

Course Introduction5 minutes
Course Syllabus10 minutes
Help Us Learn More About You15 minutes
The Case for Automation (And When to Skip It)15 minutes
Automation Self-Audit Exercise10 minutes

1 assignmentTotal 20 minutes

Module One Quiz20 minutes

1 discussion promptTotal 15 minutes

Reflect: Automation Self-Audit Exercise15 minutes

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

3 videosTotal 12 minutes

Overview of the Automation Ecosystem4 minutes
Explaining APIs4 minutes
Tool Selection Example4 minutes

4 readingsTotal 40 minutes

Why GenAI Is So Useful for Automation10 minutes
What You’re Actually Handing Over10 minutes
No-Code, Low-Code, Scripting: Picking the Right Wrench10 minutes
Guided Exploration #1: Using AI to Generate & Explain Automation10 minutes

1 assignmentTotal 20 minutes

Module Two Quiz20 minutes

1 discussion promptTotal 10 minutes

Reflect: Guided Exploration #110 minutes

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

1 videoTotal 4 minutes

Capturing & Accessing Information4 minutes

6 readingsTotal 50 minutes

Why How You Store Information Is Also Automation10 minutes
The Best System Is the One You'll Actually Use10 minutes
Guided Exploration #2: Making Information Findable10 minutes
Key Takeaways5 minutes
Post-Course Survey10 minutes
Keep Learning with Michigan Online5 minutes

1 assignmentTotal 20 minutes

Module Three Quiz20 minutes

1 discussion promptTotal 10 minutes

Reflect: Guided Exploration #210 minutes

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Instructor

Tina Lasisi

University of Michigan

3 Courses5,010 learners

Offered by

University of Michigan

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