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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.
More than two-thirds of our research is rated ‘world-leading’ or ‘internationally excellent' (REF 2014).
Professional accreditation
Accredited by BCS, the Chartered Institute for IT for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.
Accredited by BCS, the Chartered Institute for IT on behalf of the Engineering Council for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer.
Accredited by the Institution of Engineering and Technology (IET) on behalf of the Engineering Council as meeting the requirements for Further Learning for registration as a Chartered Engineer. Candidates must hold a CEng accredited BEng/BSc (Hons) undergraduate first degree to comply with full CEng registration requirements.
Why we're great.
Develop the knowledge to handle data and the skills needed to turn it into valuable, meaningful information
Gain hands-on experience – work on projects derived from the needs of our industrial partners
Our Employability and Careers Centre is on hand to help with careers advice and planning. You will also have opportunities to present your research and travel to international conferences
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 Edward Tsang – applied AI, constraint satisfaction, computational finance and economics, agent-based simulations
Specialist facilities
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 10 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
Your future
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, and now work for global companies such as Microsoft as well as regional start-ups, as software developers, development managers and product managers.
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.
Entry requirements
UK entry requirements
A 2.2 degree, or international equivalent, in: Computer Science; Computer Engineering; Computer Networks; Computer Games; Computing; Software Engineering, Electronic Engineering; Electrical Engineering; Telecommunication Engineering; Information Engineering; Automation; Mechatronic Engineering; Mathematics or Physics.
Graduates of Computer Science; Computer Engineering; Computer Networks; Computer Games; Computing; Software Engineering must have studied :
ONE maths module (e.g.Mathematics; Calculus; Algebra; Differential Equations).
and ONE other computing related module (e.g. Database, Web development, Software engineering, Operating system, Computer architecture; Computer systems etc.).
Graduates of Electronic Engineering; Electrical Engineering; Telecommunication Engineering; Automation; Mechatronic Engineering; Mathematics; Physics must have studied:
ONE maths module (e.g.Mathematics; Calculus; Algebra; Differential Equations).
and ONE other math module (e.g. Mathematics, Calculus, Algebra, Differential Equations, Probability and statistics, Signals and systems, Control theory, Control systems, Computer systems, Embedded systems, Microprocessors).
International & EU entry requirements
We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.
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where you'll find this information.
English language 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.
Additional Notes
The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.
Structure
Example structure
Most of our courses combine compulsory and optional modules, giving you freedom to pursue your own interests. All of the modules listed below provide an example of what is on offer from the current academic year. Our Programme Specification provides further details of the course structure for the current academic year.
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.
The example structure below is representative of this course if taken full-time. If you choose to study part-time, the modules will be split across 2 years.
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.
Search engines have become the first entry point into a world of knowledge and they form an essential part of many modern computer applications. While much of the underlying principles have been developed over decades, the landscape of search engine technology has changed dramatically in recent years to deal with data sources magnitudes larger than ever before (the rise of 'big data'). As a result of this, new paradigms for storing, indexing and accessing information have emerged. This module will provide the essential foundation of information retrieval and equip students with solid, applicable knowledge of state-of-the-art search technology.
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.
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.
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.
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.
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.
The aim of this module is to familiarise students with the whole pipeline of processing, analysing, presenting and making decision using data. This module blends data analysis, decision making and visualisation with practical python programming. Students will need a reasonable programming background as they will be expected to develop a complete end-to-end data science application.
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.
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.
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.
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
Assessment
Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework
Dissertation
Your research project allows you to focus in depth on your chosen topic from April
Close supervision by faculty staff
Fees and funding
Home/EU fee
£9,500
International fee
£18,460
Fees will increase for each academic year of study.
What's next
Open Days
We hold 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 tours@essex.ac.uk and we’ll arrange an individual campus tour for you.
We aim to respond to applications within two weeks. If we are able to offer you a place, you will be contacted via email.
For information on our deadline to apply for this course, please see our ‘how to apply’ information.
Visit Colchester Campus
Home to 15,000 students from more than 130 countries, our Colchester Campus is the largest of our three sites, making us one of the most internationally diverse campuses on the planet - we like to think of ourselves as the world in one place.
The Campus is set within 200 acres of beautiful parkland, located two miles from the historic town centre of Colchester – England's oldest recorded town. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.
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.
Exhibitions
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.
At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.
The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and
Ordinances and in the University Regulations, Policy and Procedures.
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