EDMIT · on edX
Probability - The Science of Uncertainty and Data
Advanced 160 hours English Professional CertificateFREE
Editor's Pick
Hand-picked by our editors as a top option in this category.
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
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Prices & availability can change — confirm on the provider's site. We're not affiliated with any single provider.
Instructor
JT
John Tsitsiklis
edX instructor
— learners— courses — instructor rating
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.
Requirements
- College-level single- and multivariable calculus
- Mathematical maturity
Who this course is for
- Aspiring data scientists and statisticians
- Engineers needing rigorous probability
- MicroMasters candidates
About this provider
ED
edX
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4.5 trust score
Frequently asked questions
Yes — you can audit it for free. A verified MITx certificate is available for a fee, and it counts toward the Statistics and Data Science MicroMasters.
Yes — it's advanced and mathematically rigorous, requiring college calculus. It's widely regarded as one of the best (and most demanding) probability MOOCs.
Probability is the theoretical foundation under machine learning, statistics and inference — this course builds it properly.
Sixteen weeks at 10–14 hours per week, instructor-paced — a substantial commitment.
No — it's self-contained, though it mirrors MIT's Introduction to Probability class and textbook.