Udemy - Monte Carlo simulations using spreadsheets

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Free Download Udemy - Monte Carlo simulations using spreadsheets
Published: 3/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 7m | Size: 550 MB
No coding experience required.

What you'll learn
Monte Carlo simulations
Confidence intervals
Probabilistic simulations
Risk management
A little game theory
Requirements
No programming skills needed.
Only basic spreadsheet knowledge.
Some mathematical (arithmetics and probability) knowledge may be handy but not required.
A spreadhseet software (Microsoft excel, google sheets, etc)
Description
Monte Carlo simulations, named after the world capital of gambling, consist on simulating individual random events belonging to a greater probabilistic system to acquire statistical trends as to how the whole system behaves based on the behaviour of its components and the relation that these components have with one another.More and more, the complexity of engineering systems and business models grow in size and complexity, making it incrisingly harder to analyze via deterministic methods. Monte Carlo simulations come into play to offer a robust and rigorous methodology to understand large and complex systems that would be, otherwise, simple impossible.During this course, we are going to learn the very basic concepts that we need in order to build our own Monte Carlo simulations for any system. Furthermore, we will be able to deliver key results that will let us get insights on to the systems likely behaviour via the confidence intervals.This course is intended to any person who wishes to add this valuable skill to their toolbet with no previous experience or knowledge whatsoever. You will only need to know the very basics of spreadsheets (either Microsoft Excel or Google Sheets) and some basic arithmetic and algebraic knowledge.
Who this course is for
Beginner level students interested in probabilistic simulations
Beginner level students looking to learn how to simulate risk management
Anyone in general who's interested in probabilistic simulations
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