Self-Teaching Is a Skill
A self-teaching methodology tutorial open-sourced by Li Xiaolai on GitHub, delivered as Jupyter Notebooks. It combines learning methodology, introductory Python programming and deliberate practice, emphasizing that self-teaching is a skill that can be decomposed and trained.
Timeline (last 90 days)
Li Xiaolai's "the-craft-of-selfteaching" has gained more than 18,000 stars on GitHub.
The project gained 143 stars today.
The project's description is: "One has no future if one couldn't teach themself."
The project uses Jupyter Notebook as its main medium, integrating learning methodology, introductory programming and deliberate practice.
The author defines self-teaching as a decomposable, trainable "craft" rather than a talent.
The project's high star count reflects a real need among self-learners, but the effectiveness of methodology-type content depends heavily on execution.
Readers need to select chapters based on their own foundation and avoid falling into the illusion that "bookmarking equals learning."
The exercises in the project are designed with an introduction to Python in mind, so learners in other fields need to make corresponding adaptations.
All Facts (8)
Li Xiaolai's "the-craft-of-selfteaching" has gained more than 18,000 stars on GitHub.
50%UnverifiedThe project gained 143 stars today.
50%UnverifiedThe project's description is: "One has no future if one couldn't teach themself."
50%UnverifiedThe project uses Jupyter Notebook as its main medium, integrating learning methodology, introductory programming and deliberate practice.
50%UnverifiedThe author defines self-teaching as a decomposable, trainable "craft" rather than a talent.
50%UnverifiedThe project's high star count reflects a real need among self-learners, but the effectiveness of methodology-type content depends heavily on execution.
50%UnverifiedReaders need to select chapters based on their own foundation and avoid falling into the illusion that "bookmarking equals learning."
50%UnverifiedThe exercises in the project are designed with an introduction to Python in mind, so learners in other fields need to make corresponding adaptations.
50%