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For those who did not know, Stanford university offered free off charge 3 courses at beginning of the autumn. It is kind of shocking – US based institution offers education for free! Take any socialism oriented country and one of the promises is education for free. But it seems, that the argument loosing the power – Stanford, khanacademy and bunch of others offer high quality learning for everyone.

In January (scroll down to get full list), Stanford will provide more than 15 courses for free and I thought that I could provide my based opinion about the courses. This course was perfect fit for my personality and I loved it. Every week there was video lessons about the topics like machine learning, datamining, and statistical pattern recognition, overview questions and programming exercises, which had to be completed in Octave/Matlab. The quality of the video was superb, the length of the lessons was 8-14 minutes and format of the lessons was great as well (Prof. Andrew Ng was seamlessly switching between the white board and talks).
This course inspired me to build anomaly detection system at my work, where we already spotted few anomalies. Now I’m working on  kind of “spam filter implementation” for text analysis.
For me, the practical part of the course is like the water for the fish – without it theoretical part is empty and to be forgotten within the hours. This course gave to me a broad view about artificial intelligence: machine learning, robotics, natural language processing, computer vision, search algorithms and etc. I suppose, that because the topics are so different the course was align towards theoretical part – otherwise the practical parts would take forever. However, in the last part there was an optional exercise – to encrypt two texts, which I loved!
The instructors, namely Sebastian Thrun and Peter Norvig, recommend this book: Artificial Intelligence: A Modern Approach. I should say, that the book was very helpful during the course and but I won’t use it outside the course.
The courses have different evaluation systems. AI class will score your homework and exams, where the top 1% will be awarded with special paper and maybe a job offer, while ML class inclined towards delivering knowledge – almost everyone working hard could get 100% score without a penalty. I think, that based on such environments, different communities sprang up – forum is very harsh to any question, where the answers start by stating, like “I know the answer, but hey, I can’t tell you anything, because honor code doesn’t allow and I’m the smartest guy on the Earth”, while ml-class forum is more open minded – if you can’t crack the problem then other students will help you.
I was in light shock, when I saw the format of AI lectures first time – the instructors used real white board, namely paper and pencil and took me a while to get use it.

But overall, I really really enjoy both courses and special thanks to Stanford professors, concretely Andrew Ng, Sebastian Thrun and Peter Norvig!

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