Built as an interactive learning platform: short lessons, live visualisations and exercises. Modules can be taken in order or on their own.
AI / ML for Practitioners
A self-paced curriculum with interactive lessons, from shared foundations through machine learning, deep learning, language, vision, time series, generative AI and MLOps.
- 01FoundationsThe AI/ML landscape, core concepts, data engineering, visualisation and ethics: the shared language every later module builds on.Interactive: Where the terms sit · A project, end to endMembers
- 02Machine learningSupervised and unsupervised methods, evaluation and the habits that keep models honest.Interactive: Bias and variance · Fitting a regressionMembers
- 03Deep learningNeural networks from first principles to modern architectures, with hands-on training.Interactive: A neural network learningMembers
- 04Natural language processingFrom tokens and embeddings to transformers and retrieval.Interactive: Words as vectors · Attention, token by tokenMembers
- 05Computer visionImage classification, detection and segmentation, and where vision models fail.Interactive: A convolution, step by step · Scoring a detectionMembers
- 06Time seriesForecasting and anomaly detection for operational data.Interactive: Forecasting and anomaliesMembers
- 07Generative AILarge language models, prompting, retrieval and agents, built and evaluated.Interactive: Retrieval for generation · Choosing the next tokenMembers
- 08MLOpsShipping, monitoring and retraining models as dependable services.Interactive: The MLOps pipeline · Drift and retrainingMembers