About the course
Our modern world is witnessing a growth of online data in a variety of forms, including web documents, blogs, social networks, digital libraries and medical records. Much of this data contains valuable information, such as emerging opinions in social networks, search trends from search engines, consumer purchase behaviour, and patterns that emerge from these huge data sources.
The sheer volume of this information means that traditional stand-alone applications are no longer suitable to process and analyse this data. Our 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 explore areas including:
- Mobile and social application programming
- Human-computer interaction
- Computer vision
- Computer networking
- Computer security
You also obtain practical knowledge of processing textual data on a large scale in order to turn this data into meaningful information, and have the chance to work on projects that are derived from actual industry needs proposed by our industrial partners.
We are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of our research rated ‘world-leading’ or ‘internationally excellent (REF 2014).
This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).
Our expert staff
Today’s computer scientists are creative people who are focused and committed, yet restless and experimental. We are home to many of the world’s top scientists, and our staff are driven by creativity and imagination as well as technical excellence. We are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.
Specialist staff working on data analytics include:
- Dr Luca Citi – machine learning, learning from biological signals and data (EEG, etc)
- Dr Adrian Clark – automatic construction of vision systems using machine learning and evaluation of algorithms, data visualisation and augmented reality
- Professor Maria Fasli – analysis of structured/unstructured data, machine learning, adaptation, semantic information extraction, ontologies, data exploration, recommendation technologies
- Professor John Gan – machine learning for data modelling and analysis, dimensionality reduction and feature selection in high-dimensional data space
- Dr Udo Kruschwitz – natural language processing, analysis textual/unstructured data, information retrieval
- Professor Massimo Poesio – cognitive science of language, text mining, computational linguistics
- Professor Edward Tsang – applied AI, constraint satisfaction, computational finance and economics, agent-based simulations
We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
- We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
- All computers run either Windows 7 or are dual boot with Linux
- Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
- Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
- We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
Demand for skilled graduates in the areas of big data and data science is growing rapidly in both the public and private sector, and there is a predicted shortage of data scientists with the skills to understand and make commercial decisions based on the analysis of big data.
Our recent graduates have progressed to a variety of senior positions in industry and academia. Some of the companies and organisations where our former graduates are now employed include:
- Electronic Data Systems
- Pfizer Pharmaceuticals
- Bank of Mexico
- Visa International
- Hyperknowledge (Cambridge)
- Hellenic Air Force
- ICSS (Beijing)
- United Microelectronic Corporation (Taiwan)
We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.
Postgraduate study is the chance to take your education to the next level. The combination of compulsory and optional modules means our courses help you develop extensive knowledge in your chosen discipline, whilst providing plenty of freedom to pursue your own interests. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field, therefore to ensure your course is as relevant and up-to-date as possible your core module structure may be subject to change.
For many of our courses you’ll have a wide range of optional modules to choose from – those listed in this example structure are, in many instances, just a selection of those available. Our Programme Specification gives more detail about the structure available to our current postgraduate students, including details of all optional modules.
What fascinates you? Apply your learning in computer science or engineering to solve a problem. Design, implement and evaluate a solution, producing a dissertation on your investigation and giving an oral presentation of your work. Test your knowledge, while gaining practical experience and building your project management skills.
View 'MSc Project and Dissertation' on our Module Directory
We now live in the era of the cloud, fifty years after John McCarthy first proposed that computing could accessed like a public utility, just as we plug a device in to an electricity socket. Cloud computing, making large-scale datacentres and their facilities publically available over the Internet, is now an economic engine of growth. It certainly generates income for the giants of the computing industry, such as Amazon, Google, Microsoft and Oracle. But it also benefits numerous small and medium-sized enterprises (SMEs) that transfer their e-commerce, Big Data, Web and business analytics, and IT applications to a cloud in a way that would have been impossible previously, because the SMEs would have lacked the start-up capital. There are also employment opportunities in third-party companies that manage clouds, help transfer applications to a cloud, and create software to run novel applications on a cloud. The module will therefore be of interest to those hoping to enter the cloud-computing industry. More specifically this module provides students with an understanding of the key architectural features and technologies of cloud computing. It investigates virtualization of resources, the service oriented architecture, large-scale data management, and networking. The module also reviews contemporary developments such as green and mobile cloud computing. A theoretical analysis of cloud technologies is supplemented by analysis of actual data-centres and services, available from major providers including Amazon, Google, and Microsoft. Practical work within the module provides students with hands-on experience of virtualization and the performance of typical applications such as video transcoding and mapReduce-based parallel computation.
View 'Cloud Technologies and Systems (optional)' on our Module Directory
Teamwork skills are essential for employability. The aim of this module is to provide students with the opportunity to apply their specialised knowledge to a realistic problem and gain practical experience of the processes involved in the team-based production of software. Wherever possible, teams are organised on the basis of shared interest, and the problem is designed to exercise their understanding of their area of specialised study. Starting from an outline description of a realistic problem, each team is required to develop a fully implemented software solution using appropriate engineering and project management techniques.
View 'Group Project' on our Module Directory
When a program ran too slowly, it used to be the case that one could simply wait a few months and improvements in the speed of processors would make it run quickly enough. Sadly, that is no longer the case and programmers must take a different approach -- and that leads us into the realm of high-performance computing. In this module, the jargon of and approaches to high-performance computing will be introduced. Lectures will cover the principles and theory of the subject, giving you knowledge of things like how to calculate how many processors will be needed to perform a particular task, while the companion practical sessions give you the chance to build a compute cluster and write programs to run on it and on the module's dedicated 100-node cluster.
View 'High Performance Computing' on our Module Directory
Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.
View 'Machine Learning and Data Mining' on our Module Directory
As humans we are adept in understanding the meaning of texts and conversations. We can also perform tasks such as summarize a set of documents to focus on key information, answer questions based on a text, and when bilingual, translate a text from one language into fluent text in another language. Natural Language Engineering (NLE) aims to create computer programs that perform language tasks with similar proficiency. This course provides a strong foundation to understand the fundamental problems in NLE and also equips students with the practical skills to build small-scale NLE systems. Students are introduced to three core ideas of NLE: a) gaining an understanding the core elements of language--- the structure and grammar of words, sentences and full documents, and how NLE problems are related to defining and learning such structures, b) identify the computational complexity that naturally exists in language tasks and the unique problems that humans easily solve but are incredibly hard for computers to do, and c) gain expertise in developing intelligent computing techniques which can overcome these challenges.
View 'Natural Language Engineering' on our Module Directory
This module aims to prepare students for conducting an independent research project leading to a dissertation and to provide them with an appreciation of research and business skills related to their professional career. As a precursor to their project students, individually select an area of Computer Science, or Electronic Engineering, or Computational Finance and perform the necessary background research to define a topic and prepare a project proposal under the guidance of a supervisor. The module guides them by a) introducing common research methods b) creating an understanding of basic statistics for describing and making conclusions from data c) helping to write a strong proposal including learning how to perform literature search and evaluation and d) giving an in-depth view into the business enterprise, financial and management accounting and investment appraisal.
View 'Professional Practice and Research Methodology' on our Module Directory
We live in an era in which the amount of information available in textual form - whether of scientific or commercial interest - greatly exceeds the capability of any man to read or even skim. Text analytics is the area of artificial intelligence concerned with making such vast amounts of textual information manageable - by classifying documents as relevant or not, by extracting relevant information from document collections, and/or by summarizing the content of multiple documents. In this module we cover all three types of techniques.
View 'Text Analytics' on our Module Directory
Want to learn about more advanced web technologies? Topics covered in this module include current server-side and client-side frameworks, relational and no-SQL databases, XML, web services and others. Student showcase their web development skills by designing and implementing a web site making use of the technologies taught in this module.
View 'Advanced Web Technologies (optional)' on our Module Directory
This course gives an introduction to computer security and cryptography, and then goes on to consider security as it relates to a single, network connected, computer. Introductory material is independent of any operating system but the consideration of tools will focus on those available for Linux, partly because its open-source nature facilitates this and partly because it is widely used on server systems. The introduction to cryptography will be used to consider its use in encryption and authentication.
View 'Computer Security (optional)' on our Module Directory
Computer vision is the discipline that tries to understand the content of images and videos. It has an extraordinarily wide range of applications; well-known ones include inspection on production lines, reading number plates, mixing live and computer-generated action in movies, and recognising faces. However, researchers are working on applications such as driverless cars, building 3D models from photographs, robot navigation, gaming interfaces, and automated medical diagnosis -- in fact, whenever you as a human looks at the world and try to understand what you see is fair game for computer vision.This module introduces you to the principles of computer vision through a series of lectures and demonstrations. You have an opportunity to learn how to use these principles and algorithms on real-world vision problems in the associated laboratories using the industry-standard toolkit, OpenCV.
View 'Computer Vision (optional)' on our Module Directory
Acquire critical and transferable skills associated with the creation and growth of new business ventures. You focus on the development process from start up to early stage growth of new ventures, new small businesses spin offs from large firms, and especially innovative, technology-based firms. You study opportunity identification, self-efficacy, ideas generation, bricolage and bootstrapping, developing business models, networking, marketing, and finance.
View 'Creating and Growing a New Business Venture (optional)' on our Module Directory
A huge industry has grown up in the last few years delivering a wide range of apps for mobile devices, including application areas such as games, social networking, information, and productivity. Given the power of modern mobile devices coupled with their range of inputs (audio, camera, GPS, motion sensor, touchscreen) this creates an exceptionally interesting platform to develop applications for. Furthermore, these platforms come complete with their own marketplaces meaning that successful applications can achieve a large market share based largely on their merit. The purpose of this module is to teach the main aspects of programming applications for such devices. Such a course could be taught at an abstract level, independent of the particular type of device in question, but the approach taken on this module is to explore one particular platform (Android), in a hands-on and in-depth manner. This is a popular platform with a range of excellent devices (including low cost ones) from a variety of manufacturers. The platform is well designed and well documented, and has the significant advantage of being Java based, meaning that students can get up to speed relatively quickly and concentrate on the interesting issues involved in developing a high quality app without having to learn a new language at the same time.
View 'Mobile & Social Application Programming (optional)' on our Module Directory
- Courses provide a thorough and up-to-date knowledge of the theory, methods and applications of computer science
- Core components combined with optional modules, to enable you to gain either in-depth specialisation or a breadth of understanding
- Our postgraduates are encouraged to attend conferences and seminars, as well as engage with the wider research community
- Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework
- Your research project allows you to focus in depth on your chosen topic from April
- Close supervision by faculty staff
UK entry requirements
We will consider applications with an overall grade of 2:2 and above.
International and EU entry requirements
We accept a wide range of qualifications from applicants studying in the EU and other countries.
for further details about the qualifications we accept. Include information in your email about the
undergraduate qualification you have already completed or are currently taking.
IELTS entry requirements
IELTS 6.0 overall with a minimum component score of 5.5
If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.
You can apply for our postgraduate courses online. You’ll need to provide us with your academic qualifications, as well as supporting documents such as transcripts, English language qualifications and certificates. You can find a list of necessary documents online, but please note we won’t be able to process your application until we have everything we need.
There is no application deadline but we recommend that you apply before 1 July for our taught courses starting in October. We aim to respond to applications within two weeks. If we are able to offer you a place, you will be contacted via email.
We hold postgraduate events in February/March and November, and open days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:
- tour our campus and accommodation
- find out answers to your questions about our courses, student finance, graduate employability, student support and more
- meet our students and staff
If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing firstname.lastname@example.org and we’ll arrange an individual campus tour for you.
If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360 degree virtual tour allows you to explore the Colchester Campus from the comfort of your home. Check out our accommodation options, facilities and social spaces.
Our staff travel the world to speak to people about the courses on offer at Essex. Take a look at our list of exhibition dates to see if we’ll be near you in the future.