Foundations
Linear algebra, probability and optimisation implemented by hand.
02 — Technology area
AI & Machine Learning
Applied machine learning with a working understanding of the mathematics — enough to debug a training run, not just to launch one.
- Topics
- 4
- Focus areas
- 4
- Linked paths
- 2
- Format
- Study · Practice · Build
Modelling
Architecture choices, training dynamics and diagnosing a model that will not learn.
Evaluation
Leakage, calibration and per-slice error analysis before any claim is made.
Serving
Latency, cost, monitoring and the operational reality of inference.
Topics covered
PythonPyTorchNLPModel evaluation
Tooling you will use
PythonNumPyPyTorchWeights trackingVector databases
Paths that include this area
Go deeper in AI & Machine Learning
Pick the path that carries this area from fundamentals through to shipped work.