MIT's rigorous probability course, part of its Statistics and Data Science programme. It is a deep, mathematical treatment of probability — the foundation for serious statistics and machine learning. Genuinely hard and time-consuming, and best for learners who are comfortable with calculus.
Good for: Mathematically comfortable learners who want a deep foundation in probability.
Less suitable if: You want an applied, light-touch course, or you are not comfortable with calculus.
Requirements: Single and multivariable calculus. This is advanced.
Realistic time: Around 160 hours; several months at a serious pace.
About this course
Probability - The Science of Uncertainty and Data is the online version of MIT's legendary probability class, refined over 50+ years. Across sixteen rigorous weeks it builds probabilistic modelling from the ground up: probability models and axioms, conditioning and independence, discrete and continuous random variables, Bayesian inference, the laws of large numbers and the Central Limit Theorem, and random processes (Bernoulli, Poisson, Markov chains).
What you'll learn
Build and reason about probabilistic models
Work with discrete and continuous random variables
Apply conditioning, independence and Bayes' rule
Use the laws of large numbers and the CLT
Perform Bayesian and least-squares inference
Model random processes (Poisson, Markov chains)
This course includes
160h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
Free to audit on edX; the verified certificate is paid and can count towards MIT's Statistics and Data Science MicroMasters.
Comparison · LBS
Compare alternatives for Probability - The Science of Uncertainty and Data
Same topic, different options. We surface the trade-offs others hide so you can pick the course that actually fits your time, budget, and goals.
The verified certificate from MITx can count towards MIT's Statistics and Data Science MicroMasters. It is a serious, recognised credential — but it reflects genuinely demanding work.
Instructor
JT
John Tsitsiklis
edX instructor
Taught by John Tsitsiklis, Professor of Electrical Engineering and Computer Science at MIT, a member of the National Academy of Engineering who has taught probability for over 15 years.
About this provider
ED
edX
Non-profit online learning platform founded by Harvard and MIT. 45M+ learners worldwide.