The fourteen guides

Fourteen university AI study guides, one per module, built for the weeks before the exam. Every chapter has a memory hook, checkpoint questions with worked answers, an examiner trap that names how weak answers lose marks, a top-marks box that shows what a first-class answer adds, a key term, a chapter summary table, flashcards for the final week and a one-page mind map. Most chapters also carry a worked example taken step by step.

Mathematics for AI

Linear Algebra, Calculus, Probability and Optimisation

Programming for AI

Python, NumPy and Vectorisation for AI

Machine Learning

Regression, Classification, Ensembles and Evaluation

Neural Networks

Backpropagation, CNNs, RNNs and Training

Deep Learning and Generative AI

Transformers, LLMs, Alignment and Prompting

Natural Language Processing

Embeddings, Transformers and Language Tasks

Computer Vision

CNNs, Detection, Segmentation and Vision Transformers

Reinforcement Learning

Markov Decision Processes, Q-Learning, Policy Gradients and Deep RL

Data Science and Data Mining

Pipelines, Clustering, Association Rules and Model Evaluation

MLOps

Pipelines, Deployment, Monitoring and Governance

AI Ethics and Responsible AI

Fairness, Privacy, Accountability and Safety

AI in Business

Strategy, Analytics, Automation and Decision-Making

AI in Finance

Machine Learning for Trading, Risk, Fraud and Forecasting

AI in Healthcare

Clinical Machine Learning, Medical Imaging, Safety and Governance

Every guide is on Kindle at $9.99 / £7.99 and free to read with Kindle Unlimited. The paperbacks are $24.99 / £19.99; AI in Healthcare is on Kindle only for now. Lecturers and module leaders can recommend a guide as a revision companion, add it to a module's recommended reading list, or ask the university library to stock the paperback.