Course instructor: Sebastian Thrun
Learn how to program all the major systems of a robotic car from the leader of the autonomous driving teams at Google and Stanford
This class will teach you the basic methods of Artificial Intelligence, including: probabilistic inference, planning and research, localization, tracking and control, all with a focus on robotics
Extensive programming examples and tasks will apply these methods in the context of self-driving car construction.
This course is offered as part of the Georgia Tech Masters in Computer Science
The updated course includes a final project, where you have to chase a runaway robot who is trying to escape!
Success in this course requires some programming experience and some mathematical fluency.
The programming in this course is done in Python
We will use some basic object-oriented concepts to model the movement and perception of the robot
If you are new to Python but have experience with another language, you should be able to acquire the syntax fairly quickly
If you are new to programming, you should consider taking Udacity's Introduction to Computing course before trying this.
The mathematics used will be centered on probability and linear algebra
You don't need to be an expert in either, but some familiarity with probability concepts (e.g
probabilities must add to one, conditional probability, and Bayes' rule) will be extremely helpful
It is possible to learn these concepts during the course, but it will take more work
Knowledge of linear algebra, although useful, is not required.
This course is online
Contacts: Contact form
