Python for Everybody, or PY4E, is Charles Severance's long running introduction to programming, and it has earned its reputation as the friendliest on ramp in the whole field. Severance, who everyone knows as Dr Chuck, teaches at the University of Michigan School of Information, and the course carries the personality of someone who has taught nervous beginners for years and clearly enjoys it. The material starts from absolute zero, variables, conditionals, loops, functions, and it moves at a pace that respects how genuinely hard the first few weeks of coding are for a newcomer. Where the course really pays off is the second half, because instead of stopping at syntax it walks you through the things that make Python useful, reading and cleaning text, pulling structured data from web APIs, parsing JSON and XML, and storing results in a small SQLite database.
That is exactly the groundwork you want before touching any AI or machine learning course, because those courses assume you can already write a script and wrangle data without panicking. The economics are hard to argue with, since the full course is free on py4e.com, there is a free companion textbook, and freeCodeCamp hosts a long single video version, while Coursera packages the same content into a five course specialization if you want the graded assignments and a certificate on a subscription. My honest caveat is about expectations. This is not an AI course, and it is not even a data science course in the modelling sense.
You will not train a model or hear the word neural network. What you get is the ability to program, which is the prerequisite almost everyone underestimates. The other fair criticism is pace and age. If you already know a language, the opening weeks will feel painfully slow, and some of the examples and tooling betray how long the course has existed.
Neither of those bothers me much for the intended audience. For a genuine beginner who wants to eventually do AI work, this remains the course I would point them to first, because it builds real confidence rather than the illusion of it.