<p>MIT 6.041/6.431 Probabilistic Systems Analysis and Applied Probability is a full undergraduate probability course published on MIT OpenCourseWare. Taught by Prof. John Tsitsiklis, it covers the modelling and analysis of random phenomena with a rigor suited to engineering and science students preparing for university-level mathematics.</p><ul><li>Cost: free; all materials published under MIT OpenCourseWare</li><li>Format: self-paced online with video lectures, recitations, tutorials, and a syllabus</li><li>Scope: roughly 90 hours across probability models, conditioning, random variables, transforms, limit theorems, Bayesian inference, and Markov chains</li><li>Assessment: problem sets and exams with full solutions provided</li><li>Audience: students comfortable with single-variable calculus; best suited to advanced JC2 or post-A-Level learners</li></ul><p>Learners can follow the lecture order on the OCW course page and work through problem sets at their own pace.</p>