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MIT 6.00.1x/2x : A Course to Close Your Computer Science Gap as a Data Scientist
Why All Data Scientists Not From Computer Science Background Should Take the Course
…my Journey into Data Science So Far
My Data Science self-education journey has always been a bit upside down. Instead of the usual Math > Computer Science > Language/Framework > Machine Learning > Deep Learning path. I took the other way around. I stumbled into Deep Learning from the fast.ai ‘Practical Deep Learning for Coders’ course first, which greatly boosted my interest and intention to learn more. Later I took the classic ‘Machine Learning’ course by Andrew Ng. (my review on these two courses here.) These are both great courses in their own merits and as I learn more and start doing my own projects, I found that my coding skills is stopping me from making solid progress. I had to stop and learn some programming concept on the fly to make sense of the important snippets in the course or GitHub. So I took the famous CS50 course by Harvard celebrity professor David J. Malan. It helped me a lot, but I still felt incompetent when it comes to Python programming, especially OOP, data structures, and algorithms, until I find MIT 6.00.1x and 6.00.2x on Edx.
