I build my personal Q&A knowledge base to store my learning notes in a question-and-answer style for various knowledge points across different domains. This includes knowledge in AI, data structures and algorithms, mathematics, and more.
Q&A Style Learning Notes
Each post in the knowledge base follows a Q&A format to explain concepts at different levels. For example, for AI concepts, there are conceptual, implementation, and mathematical levels of questions, so that readers with varying levels of expertise can benefit from the explanations:
Anyone with general knowledge can understand them.
For anyone who wants to dive into the code implementation details of the concept.
For anyone who wants to understand the mathematics behind it.
Q&A style learning notes help me better organize and retain knowledge a lot. I am a fan of Richard Feynman’s Technique, and I find that explaining concepts in a Q&A format is a great way to test my understanding and identify gaps in my knowledge.
Organising in Q&A format also makes it easier for me to review and revisit the concepts later on. When a concept comes up again in our work or studies, we are often looking for a specific answer to a specific question about that concept. Having the knowledge organized in a Q&A format allows me to quickly find the information I need without having to read through lengthy explanations.
Knowledge Graph
A learning order has to be followed to master a concept. In each concept post, I try to include a knowledge graph that shows the order of Q&As that is recommended to learn within. One Q&A may depend on the understanding of other Q&As (inside or outside the current concept), and the knowledge graph helps to visualize these dependencies.
In the future, I might include knowledge graphs that connect different concepts together to show the overall learning path across the entire knowledge base.