Modules

You will take four core modules and two optional modules depending upon your interests and career aspirations, and complete a masters-level project over the summer on a topic of your choice. Your MSc project can be on healthcare data analytics, health informatics or clinical studies or be a multidisciplinary mix of these areas. Throughout the programme, you will learn how to master sophisticated analytics techniques and professional software, including R and the tidyverse, Python, and additional software such as SQL/NoSQL databases, to handle and exploit big data, and to work as part of a project team. You will develop conceptual, and practical understanding of topics including Big Data, medical statistics and machine learning. You will gain experience of the design and analysis of health studies, and learn how to provide impactful healthcare insights from a range of medical and clinical studies. Core modules Health Data and Medical Statistics (MATH515) This module provides an introduction to health data and medical statistics, and related ethical considerations. It discusses statistical techniques for the design, analysis and interpretation of medical studies. Up-to-date professional software for analysing health data is studied. Experience in preparing a professional statistical analysis plan is provided. Machine Learning and Artificial Intelligence for Healthcare (MATH516) This module aims to introduce cutting-edge techniques in machine learning and artificial intelligence for health data analytics. All methods will be implemented using state-of-the-art software. Modelling and Analytics for Data Science (MATH501) This module gives students an understanding of modelling and analytics techniques for data science. It supplies modern data modelling toolboxes for making strategic decisions in a broad range of practical situations. It offers a hands-on introduction to Bayesian inference and machine learning. It provides additional practice in making professional presentations. Big Data and Social Network Visualisation (MATH513) Sophisticated analytics techniques are needed to visualise today's increasing quantities of big data. Up-to-date R tools including dplyr for data manipulation, ggplot2 for visualisation, and knitr/LaTeX for document presentation are studied. These are applied to database interrogation, social network visualisation and sentiment analysis. The module provides considerable experience of writing professionally documented R code using RStudio. MSc Dissertation and Research Skills (PROJ518) – This module is core but not taught You will develop research skills to propose and undertake a research project that are practically realistic and academically worthwhile. You will design and conduct a substantial research project using ethically suitable quantitative and qualitative research methods. The project will be reported through a high quality, scholarly and professional write-up, either as a formal dissertation or journal paper.

Assessment method

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Qualified teacher status (QTS)

To work as a teacher at a state school in England or Wales, you will need to achieve qualified teacher status (QTS). This is offered on this course for the following level:

• Course does not award QTS