11–20 of 167 posts
Also, intro to comp sci by Harvard's open courseware. Without these, I might've dropped out of comp sci in my second year [2]
[1] https://www.youtube.com/watch?v=kBdfcR-8hEY [2] https://www.youtube.com/watch?v=z-OxzIC6pic&list=PLvJoKWRPIu...
Convex Optimization by Stephen Boyd (Stanford EE364A) available on itunesU. There's also a CVX101 Mooc[1], but I don't how it's different from the original material. IMO it's not the topic itself, but the invaluable material for machine learning, statistics and applied mathematics. And Boyd has such a huge insight on the topic it's always a pleasure to watch his lectures. [1] https://lagunita.stanford.edu/courses/Eng…
[1] https://www.edx.org/course/artificial-intelligence-uc-berkel...
https://www.coursera.org/course/rprog - This is the best online course I've taken. Another one I am signed up for and have already done one week of lectures (preview mode) and find very applicable is https://www.coursera.org/learn/learning-how-to-learn/
Interestingly we get a lot of mixed reviews for R Prog course: https://www.class-central.com/mooc/1713/coursera-r-programmi... Learning how to learn is the best course online that any one can take.
and with the class here -
http://datagrad.blogspot.com/2013/01/my-most-recent-mooc-exp...
Convex Optimization by Stephen Boyd (Stanford EE364A) available on itunesU. There's also a CVX101 Mooc[1], but I don't how it's different from the original material. IMO it's not the topic itself, but the invaluable material for machine learning, statistics and applied mathematics. And Boyd has such a huge insight on the topic it's always a pleasure to watch his lectures. [1] https://lagunita.stanford.edu/courses/Eng…
Thanks for sharing! On iTunes U are there assignments or other course materials, or just the video lectures? I only see the videos there and I'd like to get my hands dirty practicing assignments and not just watch the lectures.
http://stanford.edu/class/ee364a/index.html http://stanford.edu/~boyd/cvxbook/
Made by the guys from The Blue Bottle, splendid tutorial!
Andrew Ng's ML Class - This makes the list because it is incredibly useful. I didn't have much background in the field and this class is a practical survey of ideas. Not a ton of depth, but exposes you to a lot of information gently.
Daphne Koller's PGM Class - This was the most rewarding. I banged my head on a lot of this material, but it was an incredible feeling when things started to click. That I was able to complete this class is a testament to Dr. Koller's excellence as an educator.
Dan Jurafsky's and Christopher Manning's NLP Class - This class was the most fun. I thought the exercises were incredibly well designed. Unlike the first two courses, the exercises were a lot more interesting. For ML and PGM, you mostly know when you have the answer and you are rewarded with 100%. NLP assignments are based on how well your system generalizes, which made me try harder to improve my systems, and helped me enjoy the course.