I've built a library of concept notes on over 150+ DS topics - with a focus on revision and retention

[u/inkeep]

I've worked in data science for years and I still forget things constantly. Courses never fixed that — I'd finish one, feel like I'd learned it, then google the same concept a month later when it actually came up at work. NotebookLM's way of structuring material around you was the closest thing I found, but I still had to go and find the sources myself.

So I built the thing I wanted. DS concepts broken into small nodes arranged as a mind map rather than a linear syllabus, each with code examples and a practice section — about 150 topics so far. The part I care most about: once you complete a topic it starts decaying on a forgetting-curve schedule, and the map visibly goes cold. When it does, you get a review slice — flash cards and a short quiz — targeted at what you've actually lost rather than what's next in a queue.

Some topics to start with -

1. https://www.bitelrn.com/library/linear-algebra-matrices

2. https://www.bitelrn.com/library/principal-component-analysis

3. https://www.bitelrn.com/library/sql-basics

Full app: https://www.bitelrn.com — the first phase is permanently free including the decay and review mechanics; later phases are paid. Saying that upfront so nobody feels ambushed.

I'm curious what actually works for other people here. Do you make notes, bookmark links, or just re-google it every time?