A large free archive of practitioner-written tutorials and explainers on machine learning, statistics, data engineering and AI, from beginner to advanced.
Why I recommend it: Quality varies by author, but the beginner explainers are among the easiest free routes into data work.
A step-by-step tutorial on building a simple AI "world model" that predicts what happens next in an environment.
Why I recommend it: Hands-on and free; assumes some Python. Written by a single contributor, so check the code as you go.
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SkillUp blog guide on choosing career credentials and certificates. The page blocked an automated check, so this description is based on its title.
Free in-depth guide from the nonprofit Probably Good on choosing a career path that creates positive impact, covering values, career capital, job options and decision-making.
Archive of Break Through Tech's AI Studio challenge projects, where university students work in teams on real machine learning problems set by partner companies.
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