I took this course a while back: Machine Learning by Andrew Ng, which has a section on recommender systems at the end, with an assignment where you build a movie recommendation system.
A few things to note:
This is a Stanford course and it's rather theory-heavy. Lots of maths, especially matrices.
All the exercises are done with Octave, a free software similar to Matlab. This means built-in support for matrices. But as most ML is done with Python these days, once you're done you'll still need to learn Python and the ML libraries.
Professor Ng has since made courses with Python and TensorFlow, which probably give an experience closer to the real-world but I haven't taken them. You can find out about them on deeplearning.ai/. One of them is a specialisation on Coursera: coursera.org/specializations/deep-...
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I took this course a while back: Machine Learning by Andrew Ng, which has a section on recommender systems at the end, with an assignment where you build a movie recommendation system.
A few things to note:
Professor Ng has since made courses with Python and TensorFlow, which probably give an experience closer to the real-world but I haven't taken them. You can find out about them on deeplearning.ai/. One of them is a specialisation on Coursera: coursera.org/specializations/deep-...