Carnegie Mellon's practical data science course, taught through lectures and an online book and notes at datasciencecourse.org. It covers machine learning, big data, APIs, and data manipulation and analysis, with less emphasis on statistics.

Commenters describe it as a current, practical intro to data science with a lot of machine learning and big data, and a good crash course for self-taught developers.

What commenters said (2)

1. Recommendscharlysl2019in “Principles and Techniques of Data Science”

   You're welcome!

   I haven't done the course yet, I've just found it. But, from the rationale video, the course seems to be more about weaving recurrent fundamental data science concepts throughout, emphasizing one particular concept or technique in each chapter, so I guess that it would make more sense to take it as a whole.

   It is intended as a "glue" course, having completed CS fundamentals and before core data science courses, like statistics, machine learning and databases, giving students a context for what lies ahead, and just enough to be dangerous and start doing data science stuff.

   If this is what you are after, you may also want to consider CMU's "Practical Data Science", which seems to have a similar approach, videos, much more machine learning and big data, and is also very current, but doesn't have such a nice companion online book (but the notes look great) and has much less statistics: http://datasciencecourse.org

   Both look like great DS intro courses from top universities, we are spoilt.

   And then, also from Berkeley, there is "Data 8", which is intended for those who want an intro to data science, but don't have any programming or college math knowledge yet; it also has a similar online book with working links to Jupyter notebooks: http://data8.org/sp19/ (and videos: https://www.youtube.com/playlist?list=PLXbeRfilLvMoC3QZKxRrp...)

2. Recommendshackermailman2018in “Ask HN: Self-taught devs, what are the best cheap resources for learning webdev?”

   LambdaSchool https://lambdaschool.com/apply/

   My advice is if lambdaschool cant be done in his schedule then do a crash course in practical data science from CMU instead.

   https://www.cs.cmu.edu/~112/schedule.html click on each topic, short youtube lecture for intro to Python3. Homework is self contained with tests.

   http://www.datasciencecourse.org/lectures/ same school, lectures also open, a crash course in manipulating APIs and data to do analysis.

   If he actually does the homework assignments he can easily go on any freelancer site and start knocking off small jobs like 'get me all these Amazon listings for X and then produce in excel format' which pay 25-100 depending on what kind of analysis they want. Enough for a portfolio to later apply to Stripe or Amazon as a junior data engineer or whatever they are called these days. Even if not interested in data or ML that course still covers a lot of web things like headers, authentication, response codes, parsing XML, sql crash course, ect. If he does like webdev the first course is still an excellent launching pad for building your own software after in any language or getting into lambdaschool

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