Udacity Introduction to Artificial Intelligence with Peter Norvig and Sebastian Thrun

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Udacity - Introduction to Artificial Intelligence
English | .MP4 | h264, yuv420p, 640x360, 30.00 fps(r) | aac, 44100 Hz, stereo | 4.42 GB
Genre: E-learning

This course will cover probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics.

What Should I Know?
Some of the topics in Introduction to Artificial Intelligence will build on probability theory and linear algebra. You should have understanding of probability theory comparable to that at our ST101: Introduction to Statistics class

Class Summary
The objective of this class is to teach you modern AI. You will learn about the basic techniques and tricks of the trade. We also aspire to excite you about the field of AI.

Syllabus
Overview of AI

Statistics, Uncertainty, and Bayes networks

Machine Learning

Logic and Planning

Markov Decision Processes and Reinforcement Learning

Hidden Markov Models and Filters

Adversarial and Advanced Planning

Image Processing and Computer Vision

Robotics and robot motion planning

Natural Language Processing and Information Retrieval

More Info

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