About the course
Probabilistic modeling is present in a large number of fields such as physics, computer science, telecommunications networks, finance, insurance, biology and medicine.
The course gives a thorough and gradual introduction to the notion of random variables, working towards understanding the law of large numbers and central limit theorem. The necessary mathematical concepts are introduced throughout the course and a number of marked exercises are proposed.
This course also provides an overview of random variable simulation methods, such as the Monte Carlo method. Interactive digital experiments are also offered, to give you a visual representation of the taught concepts.
Probability spaces (Weeks 1-3)
Random variables on a finite or countable set (Weeks 4-5)
Real-valued random variables (Weeks 6-8)
Studentsâ€™ level in mathematics should match that of a Grande Ă‰cole preparatory class or year two of a bachelorâ€™s degree, with a principal focus on analysis (differential and integral calculation, sequences and series etc.).
Format of course
The course is divided into weekly classes, comprising videos of classroom sessions, videos of exercise correction sessions and multiple-choice quizzes. A number of weeks also include classes that present the basics of random variable simulation and interactive digital experiments that are usable immediately.
Multiple-choice quizzes help you verify that you have understood the class content and allow you to obtain a certificate of attendance at the end of the course.
This class is based on the book â€śRandom: Introduction to Probability Theory and Calculusâ€ť (AlĂ©atoire, introduction Ă la thĂ©orie et au calcul des probabilitĂ©s) by Sylvie MĂ©lĂ©ard, published by Les Ă‰ditions de lâ€™Ă‰cole Polytechnique. It has kindly been provided free of charge for students of the course, in PDF format.