Postgraduate Course

MSc Artificial Intelligence and its Applications

How to apply

Overview

The details

Course: Artificial Intelligence and its Applications

Start date: October 2022

Study mode: Full-time

Maximum duration: 1 year

Location: Colchester Campus

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

Artificial intelligence (AI) is a broad area of research that uses rigorous and hands-on computational techniques to address significant problems that arise in many different disciplines, including, but not limited to, computing systems, economics, business, healthcare, games, medicine design, education and agriculture. With the rapid advance of AI, there is a growing demand for students who can understand and promote AI to all these sectors.

Our MSc Artificial Intelligence and its Applications conversion course will equip you with a skillset on AI techniques, and prepare you for meeting demand, regardless of your academic background. You will obtain a comprehensive perspective of the current developments, the needs and the potential of AI, by participating in taught modules that promote a deep understanding of AI methods together with others that deliver the necessary technical expertise.

Our course will cover areas including:

Machine learning
Data mining
Decision making
Big data

Our course will give you both theoretical and technical relevant skills, and will offer you:

the understanding of the specifics and the intricacies of AI methodologies
the ability to apply both basic and advanced AI methods
the ability to design and implement novel solutions

You will also gain transferable skills such as the ability to develop and present arguments, as well as the ability to work independently and in groups. Within our School of Computer Science and Electronic Engineering lies the very strong AI for Decision Making research group, which will offer graduates of the course networking opportunities.

This course is developed in collaboration with industry partners and public sector organisations, which include BT, Profusion, Essex County Council, Essex Police, and Suffolk County Council. Our active links with industry can broaden your employment potential and offer placement opportunities.

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.

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Chat to our staff and students

Find out what it's like to live and study at Essex from those who are already here.

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

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

With a skillset that combines both technical and analytical know-how from our School of Computer Science and Electronic Engineering, our graduates will be able to find employment in very competitive institutions in a wide range of disciplines. A career in artificial intelligence can be realised within a wide range of sectors, including health, finance, education etc, both in the public and the private sector. Examples of specific jobs held by our AI graduates include computer/data/research scientists, software developers and analysts .

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.

Read more about computer science and electronic engineering career destinations here.

Entry requirements

UK entry requirements

A 2:2 honours degree, or equivalent, in any subject.

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

Course structure

We offer a flexible course structure with a mixture of core/compulsory modules, and optional modules chosen from lists.

Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The course content is therefore reviewed on an annual basis to ensure our courses remain up-to-date so modules listed are 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 two years.

Please note that if you are studying full-time (either starting in October or January) there is no second year; you will develop your dissertation throughout the course of your single year.

We understand that deciding where and what to study is a very important decision for you. We’ll make all reasonable efforts to provide you with the courses, services and facilities as described on our website. However, if we need to make material changes, for example due to significant disruption, or in response to COVID-19, we’ll let our applicants and students know as soon as possible.

Components and modules explained

Components

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

Status	What this means
Core	You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options	You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory	You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Compulsory with Options	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Optional	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code. For example, the module code HR100-4-FY means:

100

The department or school the module will be taught by.

In this example, the module would be taught by the Department of History.

The module number.

The UK academic level of the module.

A standard undergraduate course will comprise of level 4, 5 and 6 modules - increasing as you progress through the course.

A standard postgraduate taught course will comprise of level 7 modules.

A postgraduate research degree is a level 8 qualification.

The term the module will be taught in.

AU: Autumn term
SP: Spring term
SU: Summer term
FY: Full year
AP: Autumn and Spring terms
PS: Spring and Summer terms
AS: Autumn and Summer terms

COMPONENT 01: CORE WITH OPTIONS

(60 CREDITS)

COMPONENT 02: COMPULSORY

An Approachable Introduction to Programming

(15 CREDITS)

This module will help you develop your coding skills, and assumes you have no prior coding skills. The language used will be ‘Python’, which is well known as an introductory programming language, with the ability to learn starting with a simple single line of code approach. As your coding skills develop, you will be able to review and debug simple code, as a route to developing your own code, through the assembling of coding blocks. You will have the opportunity to experience code relevant to your own course, and to develop code that is useful within your degree context.

View An Approachable Introduction to Programming on our Module Directory

COMPONENT 03: COMPULSORY

Machine Learning

(15 CREDITS)

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 on our Module Directory

COMPONENT 04: COMPULSORY

Neural Networks and Deep Learning

(15 CREDITS)

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

COMPONENT 05: COMPULSORY

Group Project

(15 CREDITS)

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

COMPONENT 06: COMPULSORY

An Approachable Introduction to Data Science

(15 CREDITS)

This module will give you skills in artificial intelligence and data science developed through themes presented by relevant experts across a range of academic departments. It is aimed at strengthening the quantitative skill set of those faced with data challenges in their future professional life.

View An Approachable Introduction to Data Science on our Module Directory

COMPONENT 07: OPTIONAL

(30 CREDITS)

COMPONENT 08: COMPULSORY

Professional Practice and Research Methodology

(15 CREDITS)

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

Teaching

Modules provide a thorough and up-to-date knowledge of the theory, methods and applications of artificial intelligence
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

On this course you are assessed mostly by coursework and projects, but this does vary from module to module
Some modules may also incorporate written examinations

Dissertation

Your research project allows you to focus in depth on your chosen topic
Close supervision by faculty staff

Fees and funding

Home/UK fee

£10,480

International fee

£20,350

Fees will increase for each academic year of study.

What's next

2022 Open Days (Colchester Campus)

Saturday, September 17, 2022

Saturday, October 22, 2022

Find out more

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.

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