They are downloadable (most are CSV) or accessible via an API. ![]() These datasets are all free to access, though a few require you to create a site login. I like to think you’ll use them as you teach yourself about Redis features. With that in mind, I offer several entertaining datasets for inspiration – from astronomy to science fiction to parking meter revenue – many of which support a range of data types. In my past, such projects have included creating dungeon master tools, food co-op ordering systems, and software developer market research. Which is to say: Why not have fun? Choose a starter project that lets you play. On the other hand, you don’t want to spend months debugging a practice application. You need to experiment with realistic coding scenarios, including edge-cases, so the starter project should represent the way you’ll use the tool in real life. Good starter projects – once you’re done with “ Hello, world,” – accomplish something, however trivial, even if they have nothing to do with work. Your motivation for learning the new skill could be anything: preparing for a career upgrade, curiosity about a hot, new programming language, or an intent to better exploit features in an existing development environment. Teaching yourself new tech skills often requires a “starter project” and data to support that project. ![]() When you experiment with a new-to-you data science skill, you need some sort of data to work with.
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