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Decision-making under uncertainty
Rating: 4.4 out of 5(47 ratings)
541 students

Decision-making under uncertainty

Practical models and frameworks to navigate ambiguity, reduce blind spots, and make confident high-stakes decisions.
Created bymicro1 .ai
Last updated 9/2025
English
English [Auto],

What you'll learn

  • Identify the difference between risk and uncertainty and avoid common decision-making pitfalls.
  • Apply mental models such as expected value, inversion, and second-order thinking to evaluate options and uncover hidden risks.
  • Use Bayesian updating to refine assumptions and adjust decisions as new evidence emerges.
  • Run adaptive decision cycles with the OODA Loop to remain effective in fast-changing environments.
  • Design and interpret decision trees and scenario plans to compare strategies and prepare for contingencies.
  • Integrate all of these tools through real-world case studies and practical exercises to build a disciplined, repeatable approach to high-stakes choices.

Course content

5 sections • 11 lectures • 1h 2m total length

  • Why decision-making under uncertainty matters4:00

    Master decision making under uncertainty by using structured tools and mental models, distinguishing risk from true uncertainty, and applying frameworks like the OODA loop and decision trees.

Requirements

  • No prior knowledge or experience is required.
  • A basic comfort with numbers is helpful but not essential.
  • A curious mindset and willingness to apply new ways of thinking to real decisions.

Description

Uncertainty is a constant in modern decision-making. Markets shift without warning, competitors move unpredictably, and the data we rely on is often incomplete or even contradictory. Yet leaders and professionals are expected to choose a course of action, and the cost of a poor decision can be significant.

This course provides a practical toolkit for navigating those moments with clarity and confidence. You will learn to distinguish between risk, where probabilities are known, and uncertainty, where outcomes are unclear. Most real-world choices fall into the latter category, and understanding this distinction is the first step toward better decisions.

You will then explore powerful mental models such as expected value, inversion, second-order thinking, and Bayesian updating. These tools will help you weigh trade-offs, identify hidden risks, and refine your thinking as new evidence emerges. The course also introduces practical frameworks including the OODA Loop and decision trees with scenario planning. These structured approaches show you how to act quickly, adapt to changing conditions, and prepare for multiple outcomes.

Through real-world case studies—including a product launch and Netflix’s content bets—you will see how these methods work in practice. By the end, you will have a disciplined, repeatable process for making smarter choices under uncertainty in business, strategy, and beyond.

Who this course is for:

  • This course is for professionals who need to make important decisions in environments where the data is incomplete and the future is uncertain. It is especially relevant for product managers, founders, investors, consultants, and team leaders who want practical models and frameworks they can apply immediately to high-stakes choices. It is also suitable for motivated learners preparing for leadership roles who want to strengthen their ability to think critically, anticipate risks, and make disciplined decisions with confidence.

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