Machine Learning with Python: From Linear Models to Deep Learning

It works through linear models, kernel machines, neural networks and reinforcement learning via hands-on Python projects rather than a tour of buzzwords, so it's for people with strong maths and Python who want real depth, and genuinely not for you if a gentle introduction is what you're after. Go in underprepared and it will overwhelm you; go in ready and it's outstanding.

You can audit it free on edX, with a paid verified certificate (typically a few hundred dollars) that forms part of MIT's MicroMasters in Statistics and Data Science — a well-regarded credential that can count toward academic credit at MIT and elsewhere, though it isn't itself a degree. That credit pathway is the reason to consider paying rather than just auditing (as of 2026).

This is a serious, graduate-adjacent treatment of machine learning: linear models, kernel machines, neural networks, and reinforcement learning, taught through hands-on Python projects rather than a survey of buzzwords. It's part of MIT's MicroMasters program in Statistics and Data Science, so it's built to the institute's own academic standard, not a simplified industry overview.