How to apply

Overview

The details

Course: Artificial Intelligence

Start date: October 2021

Study mode: Full-time

Duration: 1 year

Location: Colchester Campus

Based in: Computer Science and Electronic Engineering (School of)

This course is available to study starting in January or October, however please be aware that part-time study is only available for the October option.

This course is now closed to new applications for January 2021 entry, but you can still apply for October 2021 and January 2022 entry.

Artificial intelligence deals with the theory, design, application, and development of biologically, socially and linguistically motivated computational paradigms.

You focus on linking artificial intelligence techniques to real-world applications and projects, including artificial intelligence in business and financial applications, artificial intelligence in games, artificial intelligence in biological sciences and medicine, and artificial intelligence in industrial control.

Our unique course covers the theoretical, applied and practical aspects of artificial intelligence, with an emphasis on:

Genetic algorithms
Evolutionary programming
Fuzzy systems
Neural networks
Connectionist systems
Hybrid intelligent systems

Our School is a community of scholars leading the way in technological research and development. 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 work is driven by creativity and imagination as well as technical excellence.

More than two-thirds of our research is rated ‘world-leading’ or ‘internationally excellent (REF 2014).

This course is available on a full- and part-time basis, starting in October. You can also start this course in January, but this option is only available to those who wish to study full-time.

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.

Explore ways of linking artificial intelligence to real-world applications in a range of fields and industries
Develop a rounded understanding of theoretical, applied and practical aspects of artificial intelligence
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

THE Awards 2018 - Winner University of the Year

Our expert staff

Our research covers a range of topics, from materials science and semiconductor device physics, to the theory of computation and the philosophy of computer science, with most of our research groups based around laboratories offering world-class facilities.

Our impressive external research funding stands at over £4 million and we participate in a number of EU initiatives and undertake projects under contract to many outside bodies, including government and industrial organisations.

In recent years we have attracted many highly active research staff and we are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

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

Our course opens up employment opportunities designing intelligent software – in banks and businesses designing prediction systems, in computer games companies designing adaptive games, in pharmaceutical companies designing intelligent systems that model a given drug and its various interactions, and in heavy industries designing control systems.

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.

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 programming module (e.g. C, C#, C++, Java, Python, Object Oriented programming, Advanced Programming)
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 programming module (e.g. C, C#, C++, Java, Python, Object Oriented programming, Advanced Programming).
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.

Sorry, the entry requirements for the country that you have selected are not available here. Please select your country page 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.

Teaching and learning disclaimer

Following the impact of the pandemic, we made changes to our teaching and assessment to ensure our current students could continue with their studies uninterrupted and safely. These changes included courses being taught through blended delivery, normally including some face-to-face teaching, online provision, or a combination of both across the year.

The teaching and assessment methods listed show what is currently planned for 2021 entry; changes may be necessary if, by the beginning of this course, we need to adapt the way we’re delivering them due to the external environment, and to allow you to continue to receive the best education possible safely and seamlessly.

See full list of modules

MSc Project and Dissertation

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

Machine Learning and Data Mining

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

Professional Practice and Research Methodology

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

Group Project

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

Intelligent Systems and Robotics

This module gives an introduction to intelligent systems and robotics. It goes on to consider the essential hardware for sensing and manipulating the real world, and their properties and characteristics. The programming of intelligent systems and real-world robots are explored in the context of localisation, mapping, and fuzzy logic control.

View Intelligent Systems and Robotics on our Module Directory

Game Artificial Intelligence

This module covers a range of Artificial Intelligence techniques employed in games, and teaches how games are and can be used for research in Artificial Intelligence. The module explores algorithms for creating agents that play classical board games (such as chess or checkers) and real-time games (Mario or PacMan), including single agents able to play multiple games. The course also covers Procedural Content Generation, and explores the techniques used to simulate intelligence in the latest videogames.

View Game Artificial Intelligence on our Module Directory

Natural Language Engineering

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

Neural Networks and Deep Learning

The aim of this module is to provide students with an understanding of the role of artificial neural networks (ANNs) in computer science and artificial intelligence. This will allow the student to build computers and intelligent machines which are able to have an artificial brain which will allow them to learn and adapt in a human like fashion.

View Neural Networks and Deep Learning on our Module Directory

Creating and Growing a New Business Venture

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 on our Module Directory

Computational Models in Economics and Finance

The modules introduces students to computational thinking in economics and finance by looking at different relevant models and theories, such as agent-based modelling and game theory. Students will also be introduced to various applications, such as financial forecasting, automated bargaining and mechanism design.

View Computational Models in Economics and Finance on our Module Directory

Text Analytics

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

Data Science and Decision Making

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.

View Data Science and Decision Making on our Module Directory

Teaching

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/UK fee

£9,980

International fee

£19,380

EU students commencing their course in the 2021-22 academic year will be liable for the International fee.

Fees will increase for each academic year of study.

What's next

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.

You can apply for this postgraduate course online. Before you apply, please check our information about necessary documents that we’ll ask you to provide as part of your application.

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.

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.

How to get to Colchester Campus

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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.

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