CoursIA
An interactive Jupyter notebook curriculum for learning artificial intelligence by implementing it, moving from search and constraint algorithms through formal reasoning, game theory, machine learning, reinforcement learning, and generative AI to algorithmic trading.
CoursIA is a curriculum of interactive Jupyter notebooks for learning AI hands-on, starting from search and constraint-satisfaction algorithms and moving through formal reasoning, uncertainty, game theory, machine learning, reinforcement learning, generative AI, and algorithmic trading; some series go as far as mechanized theorem proving, rigorous model evaluation, and measuring causal emergence in a model's internal representations.
Notebooks use Python, C# with .NET Interactive, and Lean 4, with many concepts implemented as matched C#/Python twins covering the same problem and progression in both ecosystems, so a learner can separate the idea from its implementation. Series are numbered to distinguish a main path, lettered deep-dive notebooks on a given step, and separate research sub-series.
A generated COURSE_CATALOG.generated.md file tracks the exhaustive inventory, status, and maturity of every series; the README gives the pedagogical overview.