Postgraduate Course

MSc Artificial Intelligence and its Applications

How to apply

Overview

The details

Course: Artificial Intelligence and its Applications

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 (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.

The course is developed in collaboration with industry partners and public sector organisations, offering you paid work placement opportunities. Our partners include BT, Profusion, Essex County Council, Essex Police, and Suffolk County Council.

Funding for this course available

We are offering a brand new scholarship, funded by the Office for Students. Each scholarship is valued at £10,000, which can be used to pay tuition fees. These scholarships are aimed at groups of people who under-represented in the areas of Data Science and Artificial Intelligence in the UK. To apply for a scholarship, you will need to be holding an offer to study our MSc Artificial Intelligence and its Applications course. Full details about this scholarship and information on how to apply can be found on our website 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

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

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.

Entry requirements

UK entry requirements

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

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 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.

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

An Approachable Introduction to Programming

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

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

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

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

Professional Practice, Research Methodology and MSc Dissertation

This module will prepare you to conduct independent research leading to a dissertation. The module provides you with an appreciation of research and business skills which will be invaluable in your professional career. Subject areas include literature reviews, report writing, business enterprise, accounting and investment appraisal, all focused on a computer science perspective. You will also be given the opportunity to apply computer science and/or engineering principles and techniques to the solution of a practical problem involving a large project.

View Professional Practice, Research Methodology and MSc Dissertation on our Module Directory

Information Retrieval (optional)

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.

View Information Retrieval (optional) on our Module Directory

Text Analytics (optional)

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 (optional) on our Module Directory

MSc Project and Dissertation (optional)

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 (optional) on our Module Directory

Data Science and Decision Making (optional)

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 (optional) on our Module Directory

Creating and Growing a New Business Venture (optional)

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

Computational Models in Economics and Finance (optional)

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 (optional) on our Module Directory

Big-Data for Computational Finance (optional)

This module is a mix of theory and practice with big data cases in finance. Algorithmic and data science theories will be introduced and followed by a thorough introduction of data-driven algorithms for structures and unstructured data. Modern machine learning and data mining algorithms will be introduced with particular case studies on financial industry.

View Big-Data for Computational Finance (optional) on our Module Directory

MSc Industry Based Project and Dissertation (optional)

View MSc Industry Based Project and Dissertation (optional) on our Module Directory

Professional Practice, Research Methodology and MSc Dissertation

View Professional Practice, Research Methodology and MSc Dissertation 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

£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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