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Critical Thinking and Decision Science

In this Specialization, you’ll strengthen critical thinking and decision science by combining model thinking, computational problem solving, evidence-based reasoning, and practical GenAI prompting. You’ll learn how different models explain the same situation in different ways—so you can choose better assumptions, spot tradeoffs, and test strategies before you act. You’ll also practice turning messy problems into clear steps a computer could execute, using problem identification, decomposition, pattern recognition, abstraction, algorithms, and evaluation. Across lessons on statistics, the law of large numbers, correlation, experiments, prediction, cognitive biases, and logic, you’ll build habits for judging claims you see at work and in the media. You’ll then use GenAI as a thinking partner for customizing a Critical Thinking Framework, selecting and guiding models with clear constraints, and improving reliability by asking for evidence, alternatives, and checks. By the end of this Specialization, you will be able to: Apply model-based reasoning (e.g., networks, games, randomness) to explain outcomes and compare decisions. Decompose real-world problems into algorithms and evaluate solutions against goals and constraints. Judge evidence using statistical and scientific reasoning, including experiments vs. correlations and uncertainty. Build and reuse GenAI prompts that support critical thinking with explicit assumptions, sources, and evaluation steps.

Status: Critical Thinking
Status: Deductive Reasoning
IntermediateSpecialization

Top reviews across Critical Thinking and Decision Science

JS

Reviewed Feb 1, 2016

Loving this course so far, eager and excited to continue it and finish very soon. A great addition of analytical frameworks and management strategies to add to my toolkit.

AP

Reviewed May 25, 2021

A brilliant course. I had no idea about computational thinking and this course was an eye-opener. The instructors are top-notch and the learning is just amazing.highly recommended!

JI

Reviewed Nov 20, 2021

In my opinion, a must-take course. Hopefully someday it will be included as mandatory curriculum for public high schoolers all around the world.

IK

Reviewed Sep 29, 2016

A very good course. Need time to be completed. It should continue on and lectures should be available every time regarless of end of quizez or assignments.

YC

Reviewed Apr 18, 2022

It is cool and I have learnt so many things through this course . Due to this course my concept for algorithm is build strongly. Thank you for such a intersting course.

TA

Reviewed Oct 9, 2021

I benefited a lot from this course because it is easy to convey the information, really an achievement that deserves thanks to the organizers of this training course

NY

Reviewed Oct 16, 2016

This is a course for anyone who wants to be able to think logically. As an IT professional I would recommend this course to my colleagues in the Information Technology field.

JF

Reviewed May 16, 2021

I really enjoyed this course. I have learned the techniques to tackling problems (especially in a way that the computer will interpret) in this computer age.

SS

Reviewed May 3, 2020

Excellent combination of logic, statistics and psychology which is the minimum amount of understandings you need to make accurate business decisions.

RK

Reviewed Nov 18, 2019

This is a fantastic course that I would recommend to anyone interested in learning how to think better. It introduced me to many topics that i want to learn more about. Thank you, Professor Page!

PR

Reviewed May 30, 2021

The course is highly enlightening. It has helped me see that a lot of problems can be solved using computational thinking. I will recommend to anyone willing to gain knowledge in this area.

EC

Reviewed Jun 16, 2020

I have learned a lot and I am inspired to learn more. Thank you so much, University of Michigan, Coursera, and to the very insightful Professor Nesbitt.

Learner reviews across Critical Thinking and Decision Science

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Saikat
Course: Model Thinking
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3.0
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