MSc Data Science
Course Overview
This MSc in Data Science prepares you for a high-level career by providing a robust blend of theoretical knowledge and practical, marketable skills in the field. You will master topics from machine learning and statistics to programming and data visualization, with the opportunity to apply your learning in a real-world industry project. The course is accredited by BCS, The Chartered Institute for IT, providing a pathway to professional membership.
Key Program Highlights
- Comprehensive curriculum covering statistics, machine learning, programming, and data visualization
- Opportunity to undertake an industry-based collaborative project for practical experience
- Accredited by BCS, The Chartered Institute for IT, for professional recognition
- Develops in-demand skills for careers in AI, data science, and machine learning
- Equips graduates for employment in industry, commerce, and research sectors
Course Overview
This MSc in Data Science prepares you for a high-level career by providing a robust blend of theoretical knowledge and practical, marketable skills in the field. You will master topics from machine learning and statistics to programming and data visualization, with the opportunity to apply your learning in a real-world industry project. The course is accredited by BCS, The Chartered Institute for IT, providing a pathway to professional membership.
Key Program Highlights
- Comprehensive curriculum covering statistics, machine learning, programming, and data visualization
- Opportunity to undertake an industry-based collaborative project for practical experience
- Accredited by BCS, The Chartered Institute for IT, for professional recognition
- Develops in-demand skills for careers in AI, data science, and machine learning
- Equips graduates for employment in industry, commerce, and research sectors
Requirements
Modules
- MSc Project
- Big Data
- Data Visualisation
- Machine Learning
- Programming Fundamentals for Data Science
- Ethics in Data Science
- Essential Professional and Academic Skills for Masters Students
- Statistical Methods for Time Series Analysis
- Clouds, Grids and Virtualisation
- Blockchain for FinTech Applications
- Technologies for Anti-Money Laundering and Financial Crime
- Graph and Modern Databases
