The craft of building software — starting with the language that has quietly become the entry ticket to data and AI work.
Code is the common denominator under almost everything else here. For now this topic centres on Python — the readable, library-rich language most data analysis, machine learning and AI engineering is written in — which is why so many of the courses across other topics quietly assume it. Expect this area to grow as the catalog expands.
Closes the gap most aspiring AI engineers hit first — they can write a little code, but not the programming-and-maths groundwork that machine-learning material takes for granted. It walks from language basics to a working model in PyTorch, with data libraries in between.
About 52 hours
Walks the full investigative loop on real, untidy datasets — pose a question, gather and clean the data, explore it, then turn the result into a visual story an audience can act on. Each project lets you choose the dataset, so the work doubles as portfolio material.
About 43 hours
