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EnglishWhat is Open Source Data Science Masters?
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Open Source Data Science Masters is a blog that documents one attempt to go from beginner to data scientist in six months using open online resources. It is written by two people, Fras and Sabine, and its most distinctive output is a final project: a dynamic website built with the JavaScript library D3.js that tries to explain what intensive online data science study is actually like. It is worth reading if you want a first-hand account of a self-directed curriculum and how a learner's skills changed over that period — not if you are looking for a maintained course, a certification, or a current list of resources.
What the site actually is
It is a personal project log, not an institution. The site describes itself as "6 months to becoming a data scientist," and the content is organized around that single experiment rather than around ongoing publishing.
| Dimension | What the site offers |
|---|---|
| Format | Blog posts documenting a study journey |
| Authors | Fras and Sabine |
| Timeframe | A six-month study period |
| Core artifact | A D3.js-based dynamic website explaining the experience |
| Topic | Online, intensive self-study in data science |
The most recent post captured in the site's own description is dated November 23, 2014, and is titled "Final open source data science project." That date matters: treat the site as a historical record of one learning path, not as a live guide to tools or courses.
What the final project covers
The closing project is the part most readers will find useful, because it tries to answer questions that a plain curriculum list cannot:
- What is it like to study data science online, intensely, for six months?
- How does a skill set change and grow over that time?
- Which topics did the curriculum cover, and how are those topics connected to each other?
The third question is the interesting one. Mapping topics and their connections is a way of showing that data science is not a flat list of subjects — statistics, programming, and domain work feed into each other. If you are planning your own self-study, that kind of map is more useful than a syllabus, because it shows dependencies: what you need before what.
Who should spend time here
Read it if you want:
- A concrete example of structuring a six-month self-study plan
- An honest account of how skills develop during intensive online learning
- Ideas for presenting a learning journey as a data visualization project
Skip it if you want:
- A current, maintained curriculum with up-to-date tool recommendations
- A course with instruction, grading, or a credential
- A community or forum for ongoing questions
How to use it as a reference
- Read the final project post first. It summarizes the whole six-month arc, so it gives you the conclusions before the details.
- Work backwards through the posts. Earlier entries show the sequence of topics and the problems encountered along the way.
- Extract the topic map, not the tool list. The connections between subjects are the transferable part; specific libraries and platforms from 2014 are not.
- Compare the timeline against your own. Six months is an aggressive target. Use the posts to judge what pace was realistic for two people studying intensively, and adjust for the hours you can actually commit.
One caveat on the site itself: the description mentions subscribe and subscription signals but no pricing pages or payment platforms, so there is no evidence here about cost or access terms. Check the site directly if that matters to you.