Aléatoire : une introduction aux probabilités - Partie 2 (Coursera)

Offered by École Polytechnique,
Aléatoire : une introduction aux probabilités - Partie 2 (Coursera)

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. Le cours introduit graduellement la notion de variable aléatoire et culmine avec la loi des grands nombres et le théorème de la limite centrale.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Les notions mathématiques nécessaires sont introduites au fil du cours et de nombreux exercices corrigés sont proposés.
Ce cours propose aussi une introduction aux méthodes de simulations des variables aléatoires comme la méthode de Monte Carlo. Des expériences numériques interactives sont également mises à votre disposition pour vous permettre de visualiser diverses notions.

Syllabus

WEEK 1
Vecteurs aléatoires (1/2)
Nous entamons cette semaine le Cours 4 dont le sujet est les vecteurs aléatoires, c'est-à-dire, une collection finie de variables aléatoires réelles, comme par exemple des couples de variables aléatoires. Ce cours s'étend sur deux semaines.

WEEK 2
Vecteurs aléatoires (2/2)
Il s'agit de la suite et de la fin du Cours 4. Nous allons en particulier généraliser le résultat qui nous permet de faire des calculs de lois.

WEEK 3
Convergences et loi des grands nombres (1/2)
Nous entamons le Cours 5 dont l'objet principal est le théorème communément appelé la « loi des grands nombres ». Nous introduirons aussi plusieurs notions de convergence d'une suite de variables aléatoires.

WEEK 4
Convergences et loi des grands nombres (2/2)
Nous terminons le Cours 5 en donnant des exemples d'applications de la loi des grands nombres. Nous introduisons également la méthode de Monte Carlo.

WEEK 5
Fonctions caractéristiques, convergence en loi et théorème de la limite centrale (1/2)
Nous commençons le Cours 6, le dernier de ce MOOC, à cheval sur deux semaines. Cette semaine, on introduit un nouvel outil très puissant : les fonction caractéristiques.

WEEK 6
Fonctions caractéristiques, convergence en loi et théorème de la limite centrale (2/2)
Cette dernière semaine est consacrée au second pilier de la théorie des probabilités : le théorème de la limite centrale. Ce résultat nécessite une nouvelle notion de convergence : la convergence en loi. Nous verrons notamment une application aux intervalles de confiance qui sont utilisés pour les sondages.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Complexity Science (Coursera) Coursera
National University of Singapore

Introduction to Complexity Science (Coursera)

This course explores the features of complexity science. Our world is connected by an abundance of complex systems. Across all levels of organizations from physical, biological world to the social world, we may think of the connectivity between individual elements and how they interact and influence each other. For example, how humans transmit pandemics within a group, how cars interact in the traffic system and how networks connect in governmental organizations. Although these systems are diverse and different, they have surprisingly huge features in common.

Nov 30th 2026
5-12 Weeks
Calculus: Single Variable Part 2 - Differentiation (Coursera) Coursera
University of Pennsylvania

Calculus: Single Variable Part 2 - Differentiation (Coursera)

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences.

Nov 23rd 2026
3 Weeks
Public Debt Dynamics under Uncertainty (edX) EdX
International Monetary Fund - IMF,IMFx

Public Debt Dynamics under Uncertainty (edX)

This online course, presented jointly by the Institute for Capacity Development and the Fiscal Affairs Department, provides an overview of how to assess public debt dynamics under uncertainty. That is, the course discusses how to think about public debt projections when we acknowledge uncertainty about the key variables that underly debt projections (GDP growth, interest and exchange rates, and primary balances).

Self Paced
Self-Paced
Analytic Combinatorics (Coursera) Coursera
Princeton University

Analytic Combinatorics (Coursera)

Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations. All the features of this course are available for free. It does not offer a certificate upon completion.

Nov 30th 2026
5-12 Weeks
Differential Equations Part III Systems of Equations (Coursera) Coursera
Korea Advanced Institute of Science and Technology - KAIST

Differential Equations Part III Systems of Equations (Coursera)

This introductory courses on (Ordinary) Differential Equations are mainly for the people, who need differential equations mostly for the practical use in their own fields. So we try to provide basic terminologies, concepts, and methods of solving various types of differential equations as well as a rudimentary but indispensable knowledge of the underlying theory and some related applications.

Nov 30th 2026
5-12 Weeks
Supply Chain Optimization (Coursera) Coursera
University of California, Irvine

Supply Chain Optimization (Coursera)

Optimization is an important piece of an agile supply chain. In this course, we will explore the components of optimization and how to set up an optimization problem in Excel. We will also practice capacity and resource optimization and explore examples of both in the supply chain. Building off of our optimization practice, we will next learn how to use a Monte Carlo simulation to make the least risky decision in uncertain supply chain situations.

Nov 16th 2026
4 Weeks
Introduction to Mathematical Thinking (Coursera) Coursera
Stanford University

Introduction to Mathematical Thinking (Coursera)

Learn how to think the way mathematicians do - a powerful cognitive process developed over thousands of years. Mathematical thinking is not the same as doing mathematics – at least not as mathematics is typically presented in our school system. School math typically focuses on learning procedures to solve highly stereotyped problems. Professional mathematicians think a certain way to solve real problems, problems that can arise from the everyday world, or from science, or from within mathematics itself.

Nov 30th 2026
5-12 Weeks
Single Variable Calculus (Coursera) Coursera
University of Pennsylvania

Single Variable Calculus (Coursera)

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences. Distinguishing features of the course include: 1) the introduction and use of Taylor series and approximations from the beginning; 2) a novel synthesis of discrete and continuous forms of Calculus; 3) an emphasis on the conceptual over the computational; and 4) a clear, dynamic, unified approach.

Nov 23rd 2026
5-12 Weeks
Data Science: Probability (edX) EdX
HarvardX,Harvard University

Data Science: Probability (edX)

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008. In this course, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007–2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.

Self Paced
Self-Paced