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Decision Tree Analysis Course

Decision Tree Analysis Course
from 4 to 360h flexible workload
valid certificate in your country

What will I learn?

You will learn how to build and solve decision trees for sequential problems involving uncertainty, risk, and competing alternatives. The course covers probability fundamentals, Bayesian updating, and rollback analysis using expected monetary value. You will conduct sensitivity analyses, run Monte Carlo simulations, and calculate the value of perfect and imperfect information. Utility theory is introduced so you can model risk preferences beyond simple monetary outcomes. Advanced topics include capital investment decisions, multi-attribute trees, and competitive game-theoretic extensions. You will also learn how to communicate your analysis clearly to executive and technical audiences alike.

Elevify advantages

Develop skills

  • Decision Tree Construction: Build complete, well-structured decision trees from real problem statements.
  • Rollback Analysis: Apply backward induction to identify optimal decisions across multi-stage trees.
  • Sensitivity Testing: Conduct one-way, two-way, and Monte Carlo analyses to assess decision robustness.
  • Value of Information: Calculate EVPI and EVSI to justify research investments before committing to a decision.

Suggested summary

Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...
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Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.
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