How I Self-Study Data Science. My techniques and methods for learning… | by Egor Howell | Apr, 2024


Naturally, the first step in learning something is to decide what you will learn about. Most people will already have this somewhat figured out, but simply saying, “I want to learn data science,” is probably insufficient as it’s quite vague. Data science encapsulates many areas, such as maths, statistics, and coding, to state the obvious ones, but these can be broken down even further.

While it may sound mundane and a bit boring, a structured roadmap or syllabus can be a game-changer in your learning journey. It’s highly likely that someone in the field you’re interested in has shared their knowledge in a video, blog post or any other form of content. In just 10 minutes, you can have a comprehensive list of all the areas you need to study, thanks to that single piece of content. Truly amazing!

You can find these roadmaps on YouTube, Medium or a simple search engine search.

If you google something like “data science roadmap” or “software engineering roadmap,” you will get many results. Look at the top three or five and pick the one you like the look of the most.

Another method I used was while learning statistics; I visited my old university website and looked at everything they teach in the undergrad maths and physics BSc. This knowledge is open to anyone, giving me my list of statistics topics I should learn.

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