# How to use different platforms to learn Data Science? ### Youtube Content on youtube ranges from short "quick-trick" videos to 24-hour tutorial playlists. For the former if there is some topic or tool you are unfamiliar with ("What is REDIS?") youtuber **Fireship** is great at giving `100 second overview` on many tools and concepts: - SQL in 100 seconds: https://www.youtube.com/watch?v=zsjvFFKOm3c - REST API in 100 seconds: https://www.youtube.com/watch?v=-MTSQjw5DrM - GraphQL in 100 seconds: https://www.youtube.com/watch?v=eIQh02xuVw4 Some of his videos assume some prior knowledge, but he still does great job making the concepts accessible in "100 seconds" format. For something more focused and in-depth **Rob Mulla**'s long-form Pandas content is also pretty good, he assumes viewers have basic knowledge of Python needed to follow along: https://www.youtube.com/watch?v=DkjCaAMBGWM For more advanced folks, he has neat series on quick tricks to make Pandas code more idiomatic: https://www.youtube.com/watch?v=_gaAoJBMJ_Q&t=104s ### Github Reading code written by other people is probably fastest way to level-up and learn new tricks and useful patterns. When trying something new I usually try to do it myself using tutorials/documentation but if I find myself hitting a roadblock I often find it productive to visit Github to see how others are trying to solve the problem I am struggling with. ### Kaggle Platform for Machine Learning contests + rich tutorials. Main value for everyone are `datasets` and `Notebooks ` sections that have a lot examples on how to do Exploratory Data Analysis and generally "wrangle some data" into useful format. Free kaggle cloud-environments, called `kernels` are also decent alternative to `google collab`. ### Books Books quickly become outdated as software changes fast, but good books try to teach fundamental concepts that don't change as often. Everyone can write a programming book, and everyone does so end results are of varied quality, but there are two *reputable* publishers: - [Manning](https://www.manning.com/) - [O'Reilly](https://www.oreilly.com/products/books-videos.html) If you pick random book from either, there is good chance it is actually good! Both publishers offer a lot of books for free, so search web before buying! Note: O'Reilly is a publisher but also an online library that holds books from other publishers (like `Packt`) which aren't quite as well-written. [TODO - some specific Python/Pandas books (?)]