Explore our Data Analytics taught Master's degree.

P-G5PA full-time

MSc

1 year full-time

26 September 2022

Computer Science

University of Warwick

Warwick's Data Analytics MSc is designed for technically-minded graduates of computer science, mathematics or physical sciences. Ranked 2nd in the UK (REF 2014), Warwick's Computer Science department is a research leader in data analytics and will train you in the technical skills and expertise you need.

This course is designed for technically-minded graduates with a background in computer science, mathematics or the physical sciences.

It provides a distinctive perspective on data analytics that combines aspects of computer science, business, engineering and mathematics. Alongside the technical skills and expertise the course develops, this means that our graduates can pursue opportunities at the forefront of an emerging discipline that will continue to revolutionise science and industry for years to come.

The course has two components - a taught component and a dissertation. The taught component will allow you to acquire expertise and technical skills in cutting edge areas of data analytics, including computer security, data mining, natural language processing and visualisation, as well as experience of project management and scientific method.

The taught component is complemented by a dissertation project, undertaken primarily in the second half of your course, which offers the opportunity to specialise and explore areas of interest in greater depth. Your dissertation may be entirely research focussed or directed towards the application of advanced topics.

Class Size

Contact Hours

You will be assessed through a variety of methods; exams, coursework, presentations and a dissertation. Exams take place in the summer term; usually in May and/or June with dissertations expected to be completed in September.

Reading lists

Most departments have reading lists available through Warwick Library. If you would like to view reading lists for the current cohort of students you can visit our Warwick Library web page.

Your timetable

Your personalised timetable will be complete when you are registered for all modules, compulsory and optional, and you have been allocated to your lectures, seminars and other small group classes. Your compulsory modules will be registered for you and you will be able to choose your optional modules when you join us.

First Class Honours degree or a high 2:i undergraduate degree. The degree must be in Computer Science, Mathematics, Statistics, Physics, or another relevant quantitatively-focused degree.

• Band A
• IELTS overall score of 6.5, minimum component scores not below 6.0.

There are no additional entry requirements for this course.

Dissertation Project in Data Analytics

The dissertation is intended to give you the opportunity to consolidate the knowledge that you have acquired during the first half of the MSc, and to undertake a research led project. You will be expected to carry out a significant development exercise, either in the form of a research project or a knowledge transfer project that is applying recent research and the advanced topics taught in the first half of the course.

Research Methods

The module aims to facilitate the acquisition of a range of research methods, ensure that you are aware of the legal framework within which research is conducted, and that you are sensitive to the social and ethical issues which affect Computer Science/Data Analytics research.

Foundations of Data Analytics

You will study techniques for how to go from raw data to a deeper understanding of the patterns and structures within the data, to support making predictions and decision making.

Foundations of Computing

The aim of the module is to equip you with a grounding in foundations of computing and to enable you to confidently undertake a taught masters programme in advanced computing topics.

Data Mining

The module will focus on foundational concepts underlying data mining and it will introduce you to algorithms commonly used in data mining tools. You will also explore application of these tools to real-world problems.

• High Performance Computing
• Algorithmic Game Theory
• Image and Video Analysis
• Agent Based Systems
• Sensor Networks and Mobile Data Communications
• Advanced Computer Security
• Social Informatics
• Natural Language Processing

Read more about the core and optional modules offered within Computer Science on the University's module catalogue.

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