A new education venture of Stanford Prof. Sebastian Thrun, co-teacher of AI-Class
New free classes:
Start Date: 20 February
Behind the scene of AI-Class
In fact Prof. Thrun gave up tenure position at Stanford to start this new venture.
Udacity and the future of online universities
Sebastian Thrun resigns from Stanford to launch Udacity @ Kurzweil AI
It is interesting that there will be many Stanford online free classes
also coming in a few weeks, just using different "software platform" coursera
That platform is more controlled and less open, while more integrated.
As usual, life is complicated, and healthy competition is useful...
CS 101: BUILDING A SEARCH ENGINE
This class will give you an introduction to computing. In seven weeks, you will build your own search engine complete with a web crawler and way of ranking popular pages. You will understand some of the key concepts in computer science, and learn how to write your own computer programs.
No previous background in programming is expected.
Programming language used for class is apparently Python.
Python is one of most popular languages in Google (along with Java and C++)
as well as on many Computer Science and AI departments on universities.
Python is very easy to learn. The most popular book from Manning.com
Hello World! Computer Programming for Kids and Other Beginners is about Python
Week 1: How to get started: your first program Extracting a link
Week 2: How to repeat: Finding all the links on a page
Week 3: How to manage data: Crawling the web
Week 4: How to solve problems: Responding to search queries
Week 5: How programs run: Making things fast
Week 6: How to have infinite power: Ranking search results
Week 7: Where to go from here: Exam testing your knowledge
CS 373: PROGRAMMING A ROBOTIC CAR
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: Exam testing your knowledge