Modules

Machine Learning

This is a L2 module for 2nd year undergraduate students at Durham University.

Topics to be covered:

Linear Regression (one variable and multivariate), Logistic Regression, Regularisation, Decision Trees, Ensemble Learning and Random Forests, Support Vector Machines, Neural Networks, Machine Learning System Design, Data Preparation and Feature Engineering, Problem Framing, Bayesian Methods, Unsupervised Learning, Dimensionality Reduction

Recommender Systems

This is a L3 module for 3rd year undergraduate students at Durham University.

Topics to be covered:

History of recommender systems, information search and retrieval, filtering and personalising data content, users and transactions, item/user categorisation and characterisation, content-based filtering, collaborative filtering, data mining methods, context-aware methods, user similarity, matrix factorisation, alternating least squares, neighbourhood-based methods, recommender systems' challenges

Human-AI Interaction

This is a L3/L4 module, currently under construction, for students at Durham University.

Topics to be covered:

Perspectives on Human-AI Interaction, Designing AI/ML User Experience, Designing for Failure, Data and Knowledge, Data Visualization and Communication, Interpreting and Explaining Algorithms, AI Ethics, Fairness, Social Acceptability, and Trust, Human in the loop with AI/ML & Recommendations.