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Open CourseWare (OCW) refers to publicly available learning resources. OCW started back in 2002 with an initiative brought forward by MIT. Since then many top universities and research institutions started offering high quality learning materials online freely to the public. On this page I'll keep a list of useful OCW resources that I have come across.

The first online video lectures that I have studied were the MIT 18.06 Linear Algebra lectures by Gilbert Strang, who not only knows the subject but also knows how to convey it very well. It is not difficult to get very interested in the area very quickly. I have also focused my attention on an exciting area of machine learning through Stanford University's CS229 Machine Learning video lectures by Andrew Ng. The lectures are a systematic, from-ground-up, introduction to machine learning. Area specific terminology is introduced and clearly explained. This helps a lot especially when you are getting started. The lectures are well complemented by course notes with detailed derivations and descriptions that aid intuitive understanding. I am also looking forward to studding machine learning lectures by Christopher Bishop, Alex Smola, John Shawe-Taylor and others, available on videolectures.net — yet another fast growing online source of video learning resources.

OK, without further adieu, here are the links succinctly outlined:

MIT — ocw.mit.edu

• MIT 18.06 Linear Algebra video lectures by Gilbert Strang
• MIT 18.085 Computational Science and Engineering I video lectures by Gilbert Strang
• MIT 18.086 Mathematical Methods for Engineers II video lectures by Gilbert Strang

Stanford University — see.stanford.edu/SEE/courses.aspx

• Stanford CS229 Machine Learning video lectures by Andrew Ng
• Stanford EE263 Introduction to Linear Dynamical Systems video lectures by Stephen Boyd
• Stanford EE364A Convex Optimization I video lectures by Stephen Boyd
• Stanford EE364B Convex Optimization II video lectures by Stephen Boyd
• Stanford EE261 The Fourier Transform and Its Applications video lectures by Brad Osgood

Videolectures.net — videolectures.net

• Machine Learning video lectures by Christopher Bishop
• Machine Learning video lectures by Alex Smola
• Machine Learning video lectures by John Shawe-Taylor
• Machine Learning Summer Schools 2002-2009 video lectures

Happy learning!

This entry was posted on Thursday, February 5th, 2009 at 8:45 am and is filed under Signal processing, Machine learning, Linear algebra, Research, Internet. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.