Learn Data Scientist Free in 6 Months
Do end-to-end data science: collect and clean data with Python and SQL, analyze it, and build machine learning models.
Six months is enough to build a real data science foundation if you commit to it. This plan is 301 hours, about 1.7 hours a day. It moves from Python and pandas to SQL, then into serious data analysis and machine learning, and closes with Harvard's Data Science certificate, which ties the whole workflow together with proper statistics. Unlike the 3-month data science plan, this one has room for the depth (statistics, real ML) that the shorter version has to skip.
The daily math
This plan is 301 hours of free courses spread across 180 days. That works out to about 1.7 hours a day, or roughly 11.7 hours a week if you prefer to batch it. Miss a day and you make it up on the weekend; the point is a pace you can actually keep.
The plan, course by course
Why this set, and what we left out
We built this as the depth version of the 3-month data science plan, so it keeps the applied Kaggle and freeCodeCamp courses but adds the 180-hour HarvardX certificate for rigor the short plan cannot fit. We ended on HarvardX rather than opening with it because starting with hands-on tools first makes the statistics land better. We left standalone deep-learning courses out; this is a data-science path, and specialized ML belongs in the AI engineer plan.
The honest catch
This gets you the full data-science workflow and a foundation employers respect, but not senior specialization. Deep ML, experiment design at scale, and domain expertise come from real projects. Build a portfolio alongside these courses to prove it.
Keep going
Frequently asked questions
Can I become a data scientist in 6 months?
Six months of focused study builds the full workflow (Python, SQL, analysis, ML, statistics) that entry-level data roles want. Pair it with a project portfolio to be competitive.
Do I need a math background?
Comfort with algebra and basic statistics helps, and the Harvard capstone builds the statistics you need. You do not need advanced math to start.
Data scientist or data analyst first?
Data analyst roles are easier to land and this plan covers those skills early. The machine learning and statistics later in the path point you toward full data-science roles.