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Simulate with Monte Carlo

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Simulate with Monte Carlo

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

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

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

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Monte Carlo simulation turns qualitative risk assessments into quantitative probabilities, supporting data-driven decisions under uncertainty.

  • Knowing when simulation results stabilize helps assess model reliability and computational efficiency in business contexts.

  • Tornado charts and sensitivity analysis highlight the key variables affecting outcomes, enabling targeted risk mitigation.

  • Monte Carlo methods scale from simple ROI analysis to complex multi-variable scenarios, making them crucial for strategic planning.

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Recently updated!

March 2026

Assessments

7 assignmentsΒΉ

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the Statistical Inference & Predictive Modeling Foundations 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 4 modules in this course

Ready to turn uncertainty into opportunity? This Short Course was created to help data analysts master Monte Carlo simulation techniques to quantify risk and forecast outcomes under uncertainty.

By completing this course, you'll transform complex probabilistic scenarios into actionable insights. You'll build robust simulation models, conduct sensitivity analysis, and create probability distributions that inform critical business decisions with confidence. By the end of this course, you will be able to: Build Monte Carlo simulation models for project ROI analysis Evaluate sensitivity through tornado chart analysis Construct currency-exchange exposure simulations Determine optimal iteration counts for model convergence This course is unique because it combines theoretical foundations with hands-on Python implementation, providing both Excel-based and programmatic approaches to Monte Carlo modeling. To be successful in this project, you should have a background in basic statistics and Python programming.

Learners will understand the theoretical foundations of simulation modeling and prepare to build Monte Carlo models for business applications.

What's included

1 video2 readings2 assignments

1 videoβ€’Total 7 minutes
  • Building Your First Monte Carlo Model: Core Mechanicsβ€’7 minutes
2 readingsβ€’Total 14 minutes
  • Foundations of Monte Carlo Simulationβ€’8 minutes
  • Podcast: From Theory to Practice: Simulation Success Storiesβ€’6 minutes
2 assignmentsβ€’Total 15 minutes
  • Design Your First ROI Simulation Frameworkβ€’10 minutes
  • Simulation Foundations Knowledge Checkβ€’5 minutes

Learners will build functional Monte Carlo simulation models using Excel and Python, executing 10,000+ iterations to generate probability distributions for project ROI analysis.

What's included

2 videos2 readings1 assignment1 ungraded lab

2 videosβ€’Total 11 minutes
  • The Power of 10,000 Scenariosβ€’3 minutes
  • Excel Monte Carlo Implementation Essentialsβ€’7 minutes
2 readingsβ€’Total 17 minutes
  • Podcast: Excel Simulation Mastery: From Setup to Insightsβ€’7 minutes
  • Python Implementation for Advanced Simulationβ€’10 minutes
1 assignmentβ€’Total 5 minutes
  • Monte Carlo Implementation Mastery Checkβ€’5 minutes
1 ungraded labβ€’Total 20 minutes
  • Complete ROI Simulation Implementationβ€’20 minutes

Learners will master sensitivity analysis through tornado charts and convergence testing to determine optimal iteration counts for reliable simulation results.

What's included

1 video2 readings2 assignments

1 videoβ€’Total 8 minutes
  • Tornado Charts and Sensitivity Analysis Fundamentalsβ€’8 minutes
2 readingsβ€’Total 15 minutes
  • Podcast: Mastering Convergence Analysis for Reliable Simulationsβ€’6 minutes
  • Advanced Risk Modeling with Currency Exchange Applicationsβ€’9 minutes
2 assignmentsβ€’Total 15 minutes
  • Complete Sensitivity and Convergence Analysisβ€’10 minutes
  • Risk Analysis and Convergence Mastery Checkβ€’5 minutes

Learners will integrate all Monte Carlo simulation skills through comprehensive practical applications and demonstrate mastery via course-level graded assessment covering all learning outcomes.

What's included

2 videos1 reading2 assignments

2 videosβ€’Total 12 minutes
  • From Simulation to Strategic Successβ€’4 minutes
  • Integration Framework for Monte Carlo Excellenceβ€’8 minutes
1 readingβ€’Total 6 minutes
  • Podcast: Real-World Monte Carlo Success Stories and Lessonsβ€’6 minutes
2 assignmentsβ€’Total 29 minutes
  • Monte Carlo Simulation Mastery - Course Assessmentβ€’14 minutes
  • Comprehensive Monte Carlo Project Integrationβ€’15 minutes

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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ΒΉ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.