Computational Economics, Financial Markets and Policy

Our modern world is witnessing a growth of online data in a variety of forms, including web documents, blogs, social networks, digital libraries, medical records, biological data and so on. Much of this data is not fully structured but contains valuable information to uncover, like emerging opinions in social networks, search trends from search engines, consumer purchase behaviour, and patterns that emerge from these huge data sources. These developments mean traditional stand-alone applications are no longer suitable to process and analyse the amount of information available. Indeed, Google’s move from a large-scale indexed database to what is called The Knowledge Graph reflects the trend to automatically analyse data on a larger scale than before.

Our MSc Big Data and Text Analytics course equips you with the knowledge to contribute to this rapidly emerging area. We give you hands on experience with various types of large-scale data and information handling, and start by providing you with a solid understanding of the underlying technologies, in particular cloud computing and high-performance computing. You obtain practical knowledge of processing textual data, on a large scale, in order to turn this data into meaningful information. You also have the chance to work on projects that are derived from actual industry needs or proposed by our industrial partners.

A wide range of additional modules allow you to focus on aspects of big data and text analytics that most interest you, including mobile and social application programming, human-computer interaction, computer vision, computer networking and computer security, plus other areas. We prepare our graduates to enter a range of employment roles related to the wider area of information management and large-scale computing.

A Masters course is an academically rigorous programme during which you explore your subject in depth, reaching a high level of specialist knowledge. You draw on knowledge and skills from your undergraduate study or your professional life to produce work of a high academic standard, informed by current thinking and debate.
A Masters course lasts for twelve months (full-time), starting in October, and consists of taught modules during your autumn and spring terms, and normally a research-based dissertation or other project-based work submitted in September. Your balance of modules and research varies according to the subject but, typically, your research counts for 60 credits and there are 120 credits of modules, varying from 10 to 40 credits each. (If you are from the EU, then our Masters courses are regarded as ‘second-cycle’ qualifications under the Bologna Declaration and consist of 90 ECTS credits).
Please note that module information on our course finder provides a guide to course content and may be subject to review on an annual basis.

Modules

Core modules

Msc Project And Dissertation

Compulsory modules

Cloud Technologies And Systems
Group Project
High Performance Computing
Machine Learning And Data Mining
Natural Language Engineering
Professional Practice And Research Methodology
Text Analytics

Optional modules

Advanced Web Technologies
Big-Data For Computational Finance
Computer Security
Computer Vision
Creating And Growing A New Business Venture
Ip Networking And Applications
Mobile & Social Application Programming
Natural Language Engineering

Core modules must be taken and passed.
Core with options modules selected from limited lists must be taken and passed.
Compulsory modules must be taken.
Compulsory with options modules selected from limited lists must be taken.
Optional modules are selected from course specific lists.

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Accreditation

Within our School of Computer Science and Electronic Engineering, all our MSc courses have British Computer Society (BCS) and IET accreditation which is recognised worldwide.