IsraelX: Bayesian Algorithms for Self-Driving Cars

IsraelX: Bayesian Algorithms for Self-Driving Cars

It is an advanced computer science course designed to teach the essential localization algorithms used in modern autonomous vehicles. This MOOC helps students bridge the gap between classic algorithms and Bayesian localization algorithms.

Topics include the Markov assumption, Kalman filter, Histogram filter, multi-modal distributions, and particle filter programming. The course features numerous questions, exercises, and four programming assignments, allowing students to implement these algorithms themselves, thus preparing them for a career in the industry.

🆓 Free to Audit
🕒 Approx. 13 Weeks
✏️Beginner Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by Israel X
via edX

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