Monte Carlo Methods

 

 


 

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May 29th 2017

This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our “Bayesian toolbox” with more general models, and computational techniques to fit them.

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May 29th 2017

Ce cours d'introduction aux probabilités a la même contenu que le cours de tronc commun de première année de l'École polytechnique donné par Sylvie Méléard.

Average: 8 (1 vote)
Mar 7th 2017

This course is an introduction to using computation to understand real-world phenomena. This course will teach you how to use computation to accomplish a variety of goals and provides you with a brief introduction to a variety of topics in computational problem solving. This course is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity.

Average: 4.9 (8 votes)
Dec 22nd 2015

This course readies you for a career as an actuary in finance, investments, banking or insurance.

Average: 6.9 (10 votes)
Jan 20th 2014

In this course you will simulate prices of financial assets, use the Black-Scholes model to price European or Asian options, compute the Value-at-Risk of a bank and model financial time series with GARCH processes. The approach is hands-on with a strong emphasis on practical simulations that you will program, run and explore in your own computer.

Average: 9 (4 votes)