Useful quantitative models help you to make informed decisions both in situations in which the factors affecting your decision are clear, as well as in situations in which some important factors are not clear at all. In this course, you can learn how to create quantitative models to reflect complex realities, and how to include in your model elements of risk and uncertainty. You’ll also learn the methods for creating predictive models for identifying optimal choices; and how those choices change in response to changes in the model’s assumptions. You’ll also learn the basics of the measurement and management of risk. By the end of this course, you’ll be able to build your own models with your own data, so that you can begin making data-informed decisions. You’ll also be prepared for the next course in the Specialization.
This course is part of the Business and Financial Modeling Specialization
About this Course
Skills you will gain
- Microsoft Excel
Syllabus - What you will learn from this course
Week 1: Modeling Decisions in Low Uncertainty Settings
Week 2: Risk and Reward: Modeling High Uncertainty Settings
Week 3: Choosing Distributions that Fit Your Data
Week 4: Balancing Risk and Reward Using Simulation
- 5 stars70.80%
- 4 stars21.59%
- 3 stars5.83%
- 2 stars1.15%
- 1 star0.60%
TOP REVIEWS FROM MODELING RISK AND REALITIES
Sergei should be more empathic, sometimes it feels boring; despite of that the entire course is great.
I would have love to practise a little bit more of simulation.
Excellent orientation on risk and modelling. Both instructors were clear, articulate and well-organized. The modules , examples and quizzes reinforced the learning.
This course has rich theoretical and practical material if you want to study about risk and reward analysis.
Recommended for aspiring young finance or business analyst!
Great examples, the best course of the specialization so far.
Week 3 was a little bit slow. I think it was going through some theory that was already covered by course 1.
About the Business and Financial Modeling Specialization
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