“Bayesian
Algorithms for Self-Driving Cars ” is a MOOC that will boost your
skills and will prepare you for a career in the industry.
The course was designed to help students bridge the gap between
"classic" algorithms and the concept of Bayesian localization
algorithms.
We will explore topics such as the Markov assumption and which is
utilized in the Kalman filter, the concept of Histogram filter and
multi-modal distributions, the particle filter and how to efficiently
program it, and many more.
In addition to many questions and exercises, we've included also 4
programing assignments so you will be able to actually program these
algorithms for yourself.
