A Comprehensive Guide for Self-Learners in Computer Science
After taking a brief look at and reviewing the material, I would recommend that individuals use the site as a reference for each topic. This site features some of the best authors in their respective fields. Many of them I used in the past in USB back in Venezuela.
The Argument Against Self Teaching
The challenge of self-teaching in computer science lies in the fact that it often results in a weak foundation. Students might skip over certain topics, fail to complete all exercises, or merely skim through the material instead of thoroughly reading it. This can lead to significant knowledge gaps, and any project built on these foundations is likely to fall apart at the first sign of trouble.
Essential Topics in Computer Science
Topics like binary representation, mathematics, geometry, statistical analysis, operating systems, pointers, object-oriented programming, discrete mathematics, algebra, logic, set theory, compilers, databases, networks, data structures, algorithms, and complexity analysis are crucial. It is nearly impossible to teach oneself these complex subjects effectively. For instance, while one might learn CSS or HTML on their own, how can propositional logic be taught through self-study?
Computer science is highly abstract and requires reasoning to grasp. While it is not impossible to self-taught, academic guidance can significantly facilitate the learning process. In the unlikely scenario that a driven professional decides to use this as a guide to become a programmer, data scientist, or engineer, I would strongly advise the use of professional advisors to review exercises, clear doubts, and provide examples.
Furthermore, reading all the books does not guarantee a deep understanding of the subject matter or the ability to work on a professional level.
Kudos to the creators of for putting together such a valuable resource. The material they have curated looks impressive.
Assessing the Quality of
It would be challenging to give a thorough evaluation without dedicating the necessary time to review all the videos and books. However, the nine areas they list are all critically important in computer science. Anyone who has gathered free educational resources likely has their heart in the right place.
I briefly looked at the table of contents for the first book and found a wealth of valuable content. Additionally, watching the first five minutes of the video lecture suggested it being useful. I recommend checking out one or two books and videos to see if you find them interesting and informative.