A lot (and I mean a lot) of coding challenges preparing you for learning algorithms, data structures, some pointers on system design.

Also has Anki flashcards, though I do not know how effective they are considering a lot of the challenges amount to coding up a solution.

A CLI tool and an apkg template to allow you to create flashcards from markdown and have a better experience while using anki for your studies. 🌸 - GitHub - Mochitto/Markdown2Anki: A CLI tool and an apkg template to allow you to create flashcards from markdown and have a better experience while using anki for your studies. 🌸

📝 A simple markdown to anki-deck converter without any weird custom syntax - GitHub - Steve2955/md2apkg: 📝 A simple markdown to anki-deck converter without any weird custom syntax

List of resources to delve deeper into data science and/or data engineering. Very interesting suggestions and enough overlap that it's not just a 'random list'

Tool for converting markdown files into anki decks - GitHub - lukesmurray/markdown-anki-decks: Tool for converting markdown files into anki decks

Interesting reference-manager-like application (i.e. "integrated reading environment").

Interesting features:

• incremental reading (showing & remembering progress per article, allowing bookmarking automation)
• annotation sidebar (automatic creation of color-coded annotation overview, a-la Adobe Reader)
• anki card sync (allows creation of cards directly from annotations and sync to anki, with back reference to annotation context)

Converts Markdown file(s) to the Anki cards. Contribute to ashlinchak

Efficient memorization using the spacing effect: literature review of widespread applicability, tips on use & what it

This video series on how to study represents the latest in cognitive research on how people learn and Samford University professor Stephen Chew's many years of experience teaching undergraduates.

General Knowledge PKB

From previous experience, I found that I was making too many knowledge items while reading, which made it hard to identify the really important ones. So now, I read through the entire document (article PDF or chapter of a monograph) and mark down possible knowledge items (yellow highlight in citavi PDFs, pencil or 3M flags in printed materials). Then when I've finished, I write a summary knowledge item in 2 paragraphs—the first outlines the argument, the second (in italics) gives my evaluation and thoughts about possible uses. (I don't use the evaluation field in the contents tab as I want to be able to see this quickly in the knowledge view.) Now I'll go back through the marks I've made and work out which ones I want to input as knowledge items. As part of the input, I will assign to as specific category as possible. Every few days, I will have a look through my outline to see where the holes are (not a lot of knowledge items), and to see if anything in the NOT SURE YET category sparks any new thoughts on organization.