1Foundations
The maths that machine learning and computational modelling are built on.
- Linear algebra
- Calculus
- Probability
- Statistics
- Optimisation
- School maths refresher
Learn machine learning and modelling, for free.
A guided path through free courses, books and videos: start with maths and programming, then follow the machine learning track, the computational modelling track, or both.
2Programming
Programming languages and tools, algorithms and data structures, and preparing for coding interviews.
- Python and tools
- Algorithms and data structures
- Coding interviews
- R
- Julia
- MATLAB
3Machine learning
Machine learning track
Classical machine learning and the statistical view of learning from data.
- Supervised learning
- Unsupervised learning
- Model evaluation
- ML in practice
- Probabilistic and Bayesian ML
- Causal inference
- Reinforcement learning
- Data science
4Deep learning
Machine learning track
Neural networks, from first principles to transformers and language models.
- Neural network basics
- PyTorch and JAX
- Convolutional networks
- Sequence models: RNNs and LSTMs
- Transformers and language models
- Generative models
- Graph neural networks
- Interpretability
5ML for biology
Machine learning track
Applying machine learning to molecules, proteins, cells, genomes, brains and physiology.
- Molecules and drug discovery
- Proteins and antibodies
- Genomics and single-cell
- Physiological signals and healthcare
- Computational neuroscience
6Computational modelling
Computational modelling track
Modelling real systems in code: numerical methods, differential equations, dynamical systems, signals and physics-informed machine learning.
- Numerical methods
- Differential equations
- Dynamical systems and chaos
- Signal processing
- Scientific ML and physics-informed networks
+Going deeper
The mathematical thinking behind the algorithms and equations of computation and ML: for when you want to know why things work, or found you like maths more than you thought. Plus specialist topics.
- Proofs and mathematical thinking
- Discrete mathematics
- Theory of computation
- Real analysis and measure theory
- Probability theory and mathematical statistics
- Complex analysis
- Algebra and group theory
- Topology and geometry
- Stochastic processes
- More pure mathematics
Plus 7 specialist topics
Open Going deeper →+Extras
Ways to keep learning beyond the courses: reading, listening, practising, and people worth knowing about.
- Blogs and articles
- Podcasts
- Video channels
- Communities
- Practice problems
- Reading lists
- Inspiration
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