Lecture 1: Introduction to Monte Carlo algorithms

Video placeholder
View Syllabus

Skills You'll Learn

Program Development, Applied Mathematics, Algorithms, Sampling (Statistics), Computational Logic, Numerical Analysis, Physics, Markov Model, Mechanics, Quantitative Research, Mathematical Software, Linear Algebra, Simulations

Reviews

4.8 (265 ratings)

  • 5 stars
    86.03%
  • 4 stars
    11.69%
  • 3 stars
    1.13%
  • 2 stars
    0.37%
  • 1 star
    0.75%

MH

Mar 7, 2018

I really enjoyed the course. The only problem was that I was using python 3+ and the programs were written with python 2+. There are some minor differences but I figured the them easily.

LY

Mar 29, 2016

Deepen my trust in Monte-Carlo and Markov Chain Monte-Carlo simulation --- exact mimic their analytical counterpart. Also get the chance to touch the spirit of Quantum Mechanics.

From the lesson

Monte Carlo algorithms (Direct sampling, Markov-chain sampling)

Taught By

  • Werner Krauth

    Werner Krauth

    Directeur de recherches au CNRS

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.