Stanford University - CS 373: Programming a Robotic Car
WEBRip | English | FLV | 854 x 480 | AVC ~335 kbps | 29.970 fps
AAC | 123 Kbps | 44.1 KHz | 2 channels | ~7 hours | 2.06 GB
Genre: eLearning Video / Science, Programming, Cybernetics
This class, taught by one of the foremost experts in AI, will teach you basic methods in Artificial Intelligence, including: probabilistic inference, computer vision, machine learning, and planning, all with a focus on robotics. Extensive programming examples and assignments will apply these methods in the context of building self-driving cars. You will get a chance to visit, via video, the leading research labs in the field, and meet the scientists and engineers who are building self-driving cars at Stanford and Google.
Prerequisites: The instructor will assume solid knowledge of programming, all programming will be in Python. Knowledge of probability and linear algebra will be helpful.
WEEK 1:
Basics of probability
Car localization with particle filters
WEEK 2:
Gaussians and continuous probability
Tracking other cars with Kalman filters
WEEK 3:
Image Processing and Machine Learning
Finding objects in sensor data
WEEK 4:
Planning and search
Determining where to drive with A* search
Finding optimal routes with dynamic programming
WEEK 5:
Controls
Controlling steering and speeds with PID
WEEK 6:
Putting it all together
Programming a self-driving car
WEEK 7:
Final Exam
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