Teaching Responsibility
LJMU Schools involved in Delivery:
Computer Science and Mathematics
Learning Methods
Lecture
Practical
Seminar
Module Offerings
7021DATSCI-JAN-CTY
Aims
The module aims to develop skills in machine learning and data mining, using methods from computational learning theory and artificial intelligence to extract previously unknown relationships from large data sets.
Learning Outcomes
1.
Synthesise machine learning and data mining methods to extract previously unknown relationships in data.
2.
Evaluate suitable machine learning and data mining methods based on the type of data and problem to be addressed.
3.
Critically analyse the effectiveness of different machine learning and data mining methods.
Module Content
Outline Syllabus:1. Introduction
2. Supervised learning
3. Artificial neural networks
4. Support vector machines and kernel methods
5. Tree-based methods and ensemble learning
6. Deep learning
7. Unsupervised learning
8. Advanced topics in machine learning and data mining
Module Overview:
This module aims to develop skills in data mining, using methods from computational learning theory and artificial intelligence to extract previously unknown relationships from large data sets.
This module aims to develop skills in data mining, using methods from computational learning theory and artificial intelligence to extract previously unknown relationships from large data sets.