AI Wranglers course reader
Course lectures now open with Foundation-style Read, Slides, and Interactive modes, persistent annotations, fullscreen and PDF controls, and the integrated AI Tutor. Dedicated playgrounds retain the interactive reader.
Numerical Analysis
Algorithms for numerical approximation and mathematical analysis.
Linear Algebra
Master vectors, matrices, and linear transformations. The foundation of ML.
Probability & Statistics
Understand uncertainty, distributions, and data analysis.
Machine Learning
From regression to deep neural networks.
Generative Modelling
Create new data with GANs, VAEs, and Diffusion models.
Optimization Methods
Convex optimization, gradient descent, and beyond.
Optimization on Manifolds
Optimization on curved spaces and Riemannian geometry.
Sequential Decision Making
Dynamic Programming, RL, and Multiagent Systems.
Parallel Computing
HPC, GPU programming, and distributed systems.
Physics Inspired NN
Solving differential equations with deep learning.
Reasoning Models
Chain of thought, logical reasoning, and planning in AI.
Safety & Alignment
Ensuring AI systems are safe, robust, and aligned with human values.
Numerical Algorithms
Error analysis, root finding, and computational methods.
Discrete Structures
Logic, Sets, Graphs, and the math of Computer Science.