- De www.edx.org
Probability - The Science of Uncertainty and Data
- 16 sequências
- Advanced Level
- Começa em 14 maio 2023
- Termina em 3 setembro 2023
Detalhes do curso
Programa de Estudos
Unit 1: Probability models and axioms
- Probability models and axioms
- Mathematical background: Sets; sequences, limits, and series; (un)countable sets.
Unit 2: Conditioning and independence
- Conditioning and Bayes' rule
- Independence
Unit 3: Counting
- Counting
Unit 4: Discrete random variables
- Probability mass functions and expectations
- Variance; Conditioning on an event; Multiple random variables
- Conditioning on a random variable; Independence of random variables
Unit 5: Continuous random variables
- Probability density functions
- Conditioning on an event; Multiple random variables
- Conditioning on a random variable; Independence; Bayes' rule
Unit 6: Further topics on random variables
- Derived distributions
- Sums of independent random variables; Covariance and correlation
- Conditional expectation and variance revisited; Sum of a random number of independent random variables
Unit 7: Bayesian inference
- Introduction to Bayesian inference
- Linear models with normal noise
- Least mean squares (LMS) estimation
- Linear least mean squares (LLMS) estimation
Unit 8: Limit theorems and classical statistics
- Inequalities, convergence, and the Weak Law of Large Numbers
- The Central Limit Theorem (CLT)
- An introduction to classical statistics
Unit 9: Bernoulli and Poisson processes
- The Bernoulli process
- The Poisson process
- More on the Poisson process
Unit 10 (Optional): Markov chains
- Finite-state Markov chains
- Steady-state behavior of Markov chains
- Absorption probabilities and expected time to absorption
Pré-requisito
College-level calculus (single-variable & multivariable). Comfort with mathematical reasoning; and familiarity with sequences, limits, infinite series, the chain rule, and ordinary or multiple integrals.
Instrutores
John Tsitsiklis
Professor, Department of Electrical Engineering and Computer Science
MIT
Patrick Jaillet
Professor, Electrical Engineering and Computer Science
MIT
Dimitri Bertsekas
Professor, Electrical Engineering and Computer Science
MIT
Karene Chu
Digital Learning Scientist and Research Scientist
Massachusetts Institute of Technology
Qing He
Teaching Assistant
MIT
Eren Can Kizildag
Teaching Assistant
MIT
Jimmy Li
Teaching Assistant
MIT
Jagdish Ramakrishnan
Teaching Assistant
MIT
Katie Szeto
Teaching Assistant
MIT
Kuang Xu
Teaching Assistant
MIT
Editor
O Massachusetts Institute of Technology (MIT) é um instituto de investigação e uma universidade americana especializada em ciência e tecnologia. Situado em Cambridge, Massachusetts, nos arredores de Boston, no nordeste dos Estados Unidos, o MIT é frequentemente considerado como uma das universidades mais importantes do mundo.
Publica a Technology Review, uma revista científica dedicada à engenharia, ciência e inovação.
Plataforma
EdX est une plateforme d'apprentissage en ligne (dite FLOT ou MOOC). Elle héberge et met gratuitement à disposition des cours en ligne de niveau universitaire à travers le monde entier. Elle mène également des recherches sur l'apprentissage en ligne et la façon dont les utilisateurs utilisent celle-ci. Elle est à but non lucratif et la plateforme utilise un logiciel open source.
EdX a été fondée par le Massachusetts Institute of Technology et par l'université Harvard en mai 2012. En 2014, environ 50 écoles, associations et organisations internationales offrent ou projettent d'offrir des cours sur EdX. En juillet 2014, elle avait plus de 2,5 millions d'utilisateurs suivant plus de 200 cours en ligne.
Les deux universités américaines qui financent la plateforme ont investi 60 millions USD dans son développement. La plateforme France Université Numérique utilise la technologie openedX, supportée par Google.