Program Overview

Data Analytics and Statistical Machine Learning

The Data Analytics and Statistical Machine Learning program is a postgraduate course that aims to provide students with an in-depth understanding of the state of the art in data integration, mining, and analysis with applications in biology and biomedicine.

Module Overview

The module covers topics related to data, including:

• Data types
• Data modelling
• Data management
• Semantic representation
• Integration
• Analysis It will include various statistical techniques, such as:
  • Frequentist and Bayesian approaches
  • Univariate and multivariate analysis
  • Specific statistics definition Furthermore, it will present Modelling and Optimisation approaches to deal with large structured, yet heterogeneous, datasets and will include several techniques, such as:
  • Hidden Markov Models
  • Self Organizing Maps
  • Boot-strapping and resampling procedures
  • Agent-based modelling
  • Statistical Machine Learning The module will also provide methods to analyze, visualize, and integrate various types of data.

Learning Outcomes

By the end of the module, students should be able to:

• Demonstrate a good understanding of the complexity of omics and clinical data and their management, including their semantic representation
• Demonstrate an in-depth understanding and ability to perform Data integration, mining, and analysis
• Demonstrate conceptual understanding of Computing, Algorithmic, and Programming that enables the student to evaluate methodologies and develop critiques of them and, where appropriate, propose new methods
• Deal with the complexity of information available to enable the integration of diverse data types
• Demonstrate self-direction and originality in tackling and solving problems to perform the appropriate Modelling and Optimization

Credits and Assessment

The module is worth 20 credits and will be assessed through:

• Essay (60%)
• Presentation (40%)

Academics Involved

The module lead is Professor Georgios Gkoutos, whose interest is in the general areas of clinical and biomedical informatics, computational biology, and integrative and translational research aiming at the discovery of molecular origins of human disease and the development of novel diagnostic and intervention strategies.

Program Availability

Please note that this module is only available as part of MSc Bioinformatics and the International Doctoral Training Programme.