11326 modules
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ARTD6279 2025-26
MACC Final Project
This module is the culmination of your studies on the MA Contemporary Curating programme, affording you the opportunity to demonstrate the theoretical and practical approaches to curation you have developed.
Through tutorials and seminars, but primarily through independent practice, students will be supported in this module in their development of realisations of their individual curatorial interests, exploring experimental techniques and attitudes, demonstrating the knowledge, skills and relationships built over the course of the programme.
You will deliver an in-depth written academic dissertation, realise a documented project or submit a fully-detailed project proposal for a designated space. -
MATH3097 2028-29
Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined, and then demonstrated using various machine learning methods and appropriate data sets. -
STAT6143 2027-28
Machine Learning
The module aims to equip students with the necessary foundations to make practical and effective use of machine learning methods on complex datasets. This course uses R and is delivered as an intensive one-week module for the MSc in Data Analytics for Government. -
STAT6143 2028-29
Machine Learning
The module aims to equip students with the necessary foundations to make practical and effective use of machine learning methods on complex datasets. This course uses R and is delivered as an intensive one-week module for the MSc in Data Analytics for Government. -
STAT6121 2025-26
Machine Learning
The module aims to equip students with the necessary foundations to make practical and effective use of machine learning methods on complex datasets. This course uses R and is delivered as an intensive one-week module for the MSc in Data Analytics for Government. -
MATH6168 2029-30
Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined, and then demonstrated using various machine learning methods and appropriate data sets. -
MATH3097 2029-30
Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined, and then demonstrated using various machine learning methods and appropriate data sets. -
MATH6168 2026-27
Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined, and then demonstrated using various machine learning methods and appropriate data sets. -
MATH3097 2027-28
Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined, and then demonstrated using various machine learning methods and appropriate data sets. -
MATH6168 2027-28
Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined, and then demonstrated using various machine learning methods and appropriate data sets.