// the find
llSourcell/Learn_Data_Science_in_3_Months
This is the Curriculum for "Learn Data Science in 3 Months" By Siraj Raval on Youtube
A curriculum repo from 2018 that maps out a 12-week self-study path through Python, ML, and data engineering using third-party courses from EdX, Udacity, and Kaggle. It's a reading list, not a course — all the actual content lives elsewhere. Aimed at career-changers who want a structured sequence rather than figuring out the order themselves.
The three-month structure is sensible and the sequencing is reasonable — Python and stats before ML, ML before big data tooling. Pointing people at Kaggle competitions as milestone projects is good advice; it forces you to ship something. The math cheat sheet links in Month 2 are genuinely useful references.
The repo is a single README file with no code, no exercises, and no original content. Several of the linked courses have been retired or moved since 2018 — EdX URLs in particular have a bad survival rate. Hadoop and MapReduce as Week 2 of Month 3 is an odd choice in 2024 when most data engineers never touch them directly. Last updated 2020, so the tool recommendations haven't aged well: no mention of pandas, scikit-learn, or modern Python tooling anywhere in the curriculum.