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Artificial Intelligence MSc

2024-25 (also available for 2025-26)

This course is eligible for Master's loan funding. Find out more.

Start date

16 September 2024

6 January 2025

Duration

1 year full-time

Places available (subject to change)

30

About the course

Reasons to study

  1. Exciting Career Prospects - 88.2% of our graduates from the School of Computing and Engineering were in work or further study 15 months after graduation*. 
  2. Latest knowledge - You will be taught by academic staff who have world-leading expertise in research that applies AI methods to solve key societal challenges, meaning you'll develop knowledge and skills that are current and highly relevant to industry. 
  3. This course is accredited by the British Computer Society (BCS), the Chartered Institute for the IT industry. This gives you a potential advantage when looking for a job as some employers may ask for
    graduates with accredited degrees.

*HESA Graduate Outcomes 19/20 

In the UK, we have seen a huge expansion in artificial intelligence (AI) during the last decade, showcasing that the country’s economy is aiming to use intelligent technologies to position itself at the forefront of the digital revolution.

Data shows that the AI sector is worth over £15.6bn and employs more than 35,000 people.* This means that AI has rapidly become a medium-sized sector in the UK and has the potential to participate in other sectors' growth.

You could contribute to this growth by enrolling onto our Artificial Intelligence MSc at The University of Huddersfield.

Why study Artificial Intelligence MSc at Huddersfield?

Demand for AI talent in AI techniques, such as machine learning, is increasing rapidly.

There is a need to ensure the skills pipeline can meet the needs of industry now and in the future. This course aims to develop your knowledge and understanding to an advanced level across a range of areas, including:

  • Autonomous systems
  • Knowledge representation and reasoning
  • Data mining
  • Machine learning
  • Robotics

Research plays an important role in informing all our teaching and learning activities. Our academic staff are active in research that applies Artificial Intelligence methods to solve key societal changes in areas such as healthcare, transportation and smart cities. Our research expertise spans the whole spectrum of modern AI, from automated planning and knowledge representation and reasoning, to statistical and data-driven AI and machine learning.

We will equip you with an understanding of the fundamental approaches to implementing intelligent behaviour in machines. This should then enable you to match applications with appropriate AI techniques for their solution. You will also be able to construct and configure solutions using a range of AI technologies.

This course is fully accredited by the British Computer Society (BCS), the Chartered Institute for IT, and by completing it, you will have partially fulfilled the academic requirements for registration as a Chartered IT Professional.

A vibrant town, Huddersfield is a friendly and diverse place from which to study, offering lots to do between lectures.

We also offer this course as a part-time Distance Learning route.

*thedatacity.com

Course detail

Effective Research and Professional Practice

This module aims to provide you with skills that are key to helping you become a successful computing researcher or practitioner. You'll get the opportunity to study topics including the nature of research, the scientific method, research methods, literature review and referencing. The module aims to cover the structure of research papers and project reports, reviewing research papers, ethical issues (including plagiarism), defining projects, project management, writing project reports and making presentations.

Autonomous and Autonomic Intelligent Systems

Autonomous systems are intelligent systems that can act independently to accomplish goals based on their knowledge and understanding of their environment and the tasks they have to complete. This module aims to cover the background and requirements for intelligent systems autonomy in a wide range of applications, taken from a computer science and software-oriented viewpoint. As well as the technical challenges of system autonomy, you’ll get the opportunity to study ethical and legal issues, and human factors implications.

Data Mining

Data mining is a collection of tools, methods and statistical techniques for exploring and extracting meaningful information from large data sets. It is a rapidly growing field due to the increasing quantity of data gathered by organisations. There is a potential high value in discovering the patterns contained within such data collections. In this module you will look at different data mining techniques and use appropriate data-mining tools in order to evaluate the quality of the discovered knowledge. You will study approaches to preparing data for exploration, supervised and un-supervised approaches to data mining, exploring unstructured data and the social impact of data mining. You will be expected to develop your knowledge such that you are able to contribute to discussions around current application areas and research topics and to increase your background knowledge and understanding of issues and developments associated with data mining.

Knowledge Representation and Reasoning

Knowledge representation and reasoning (KR) is the field of artificial intelligence dedicated to representing information about the world in a form that computer systems can manipulate and utilise to solve complex tasks such as making decisions, diagnosing a medical condition, finding suitable answers to queries or having a dialog in a natural language. This module will introduce you to KR principles, languages and algorithms and help you gain experience in using them to solve practical problems. You will also learn about applications such as the semantic web and knowledge graphs which have found deployment in big corporations such as Google and Amazon.

Machine Learning

Machine Learning techniques are now used widely in a range of applications either stand-alone or integrated with other AI techniques. The Machine Learning module allows you to obtain a fundamental understanding of the subject as a whole: how to embody machines with the ability to learn how to recognise, classify, decide, plan, revise, optimise etc. You will learn which machine learning techniques are appropriate for which learning problem, and what the advantages and disadvantages are for a range of ML techniques. We will consider the widely known data-driven approaches, and specific techniques such as “deep learning”, and investigate the typical applications and potential limitations of these approaches. We will introduce available tools and use them in practical classes, evaluating learning bias and characteristics of training sets. High profile applications of data driven, stand-alone, ML systems will be investigated, such as the AlphaGo method. Where data is sparse, and knowledge is already present in a system, we will investigate methods to improve heuristics of existing AI systems, and to learn or revise domain knowledge. This is essentially the area of model-driven ML, where is often integrated to other reasoning systems.

Case Studies in Data Analytics and Artificial Intelligence

The purpose of this module is to enable you to appreciate the historical, current and future application areas of Artificial Intelligence and Data Analytics in relation to both theoretical and practical aspects and to investigate at least one application area in depth. Case studies discussed in the sessions will provide an exploration of applications in a variety of different areas and will be achieved by combinations of study of current research papers, tutors’ own research & the investigative work of the students within the module.

Robotics

The Robotics module allows you to gain specialist knowledge in robotic devices and autonomous applications by examining the integration of mechanical devices, sensors and ‘intelligent’ computerised robotic agents. You will also explore the latest developments in robotics and intelligent systems through a series of investigative tasks and practical sessions. The module covers essential techniques for the design and development of robotic based systems using a collection of robotic hardware and simulation software. It supports the discussion and analysis of the hardware and software used to build real-world robotic systems. It introduces device and architectural specific topics required to enable students to design and develop software for intelligent autonomous robots. This will include low-level programming of I/O devices for robotic swarms, sensor systems and active modelling and simulation. It will introduce planning for intelligent robots taking a lifecycle approach from theory to activation.

Artificial Intelligence Planning

This module will recap on the history of automated planning from the days of STRIPS, up to the present day. It will focus on the kinds of assumptions, algorithms, heuristics and representation languages that have been used to create generative planning algorithms. It will illustrate these developments using a range of planning engines and planning platforms. Current application areas and research topics in automated planning, such as hybrid planning, will be discussed and students will be expected to develop their knowledge such that they are able to contribute to such discussions and to increase their background knowledge and understanding of issues and developments associated with AI Planning.

Individual Project

This module enables you to work independently on a project related to a self-selected problem. A key feature in this final stage of the course is that you will be encouraged to undertake an in-company project with an external Client. Where appropriate, however, the Project may be undertaken with an internal Client - research-active staff - on larger research and knowledge transfer projects. The Project is intended to be integrative, a culmination of knowledge, skills, competencies and experiences acquired in other modules, coupled with further development of these assets. In the case where an external client is involved, both the Client and Student will be required to sign a learning agreement that clearly outlines scope, responsibilities and ownership of the project and its products or other deliverables. The Project will be student-driven, with the clear onus on you to negotiate agreement, and communicate effectively, with all parties involved at each stage of the Project.

Entry requirements

Entry requirements for this course are normally:

  • A BSc or BEng Honours degree (2:2 or above) in Computing or Engineering or related subject or an equivalent professional qualification
  • Other qualifications and/or experience that demonstrate appropriate knowledge and skills at an Honours degree level

If your first language is not English, you will need to meet the minimum requirements of an English Language qualification. The minimum for IELTS is 6.0 overall with no element lower than 5.5, or equivalent. Read more about the University’s entry requirements for students outside of the UK on our Where are you from information pages.

Why Huddersfield?


Find out why some of our students chose to study with us. From feeling at home as soon as they came to campus, to the fantastic facilities, friendly community and engaging courses.

Enhance your career


We would expect to see graduates progress to careers as Robotics Programmer, Machine Learning Engineer, Data Mining Analyst or Software Engineer for example. You could also go on to further study and the University has many options available for postgraduate research which may interest you.**

*  Percentage of graduates from the School of Computing and Engineering who are in work and/or further study fifteen months after graduating (HESA Graduate Outcomes 19/20, UK domiciled graduates)

** Source: LinkedIn

88.2%*

Student support

At the University of Huddersfield, you'll find support networks and services to help you get ahead in your studies and social life. Whether you study at undergraduate or postgraduate level, you'll soon discover that you're never far away from our dedicated staff and resources to help you to navigate through your personal student journey. Find out more about all our support services.

A wide range of resources are also offered within the School of Computing and Engineering, which provides you with support in a variety of areas. These include:

Student Support Office: A one stop shop for students studying within the School. The team deal with every aspect of student life from enrolment, module queries, timetabling, exams, assessments, course-related committees and graduation. They are the first place to go with any query, and they can also signpost to other support networks.

Student Guidance Office: Students can book an appointment with a Guidance Adviser at any time during their studies; we are here to help with navigating any challenges they may face while studying. Our Advisers are skilled in providing advice and guidance to students on a range of issues including personal circumstances and academic issues and can help students to understand University regulations. The Guidance Team also offer study skills appointments to support with developing academic skills, such as; research and project planning, referencing and paraphrasing, essay writing, critical thinking, understanding assessments and to develop Maths skills. The team also encourage students to develop effective study habits such as good time management to meet deadlines by supporting with planning and organising work schedules.

Technical Support: technicians support our students across each department. Based in our labs with different specialisms and knowledge they are on hand to provide support, guide and advise where students can access our technician’s expertise/knowledge during lectures and seminars as well as during self-study. An IT Support Helpdesk is also available to all students within the School of Computing and Engineering to help troubleshoot any computer issues/problems or to loan hardware and software.

Important information

We will always try to deliver your course as described on this web page. However, sometimes we may have to make changes as set out below.

Changes to a course you have applied for

If we propose to make a major change to a course that you are holding an offer for, then we will tell you as soon as possible so that you can decide whether to withdraw your application prior to enrolment.

Cancellation of a course you have applied for

Although we always try and run all of the course we offer, we may occasionally have to withdraw a course you have applied for or combine your programme with another programme if we consider this reasonably necessary to ensure a good student experience, for example if there are not enough applicants to ensure you have a good learning experience. Where this is the case we will notify you as soon as reasonably possible and we will contact you to discuss other suitable courses with us we can transfer your application to. If we notify you that the course you have applied to has been withdrawn or combined, and you do not wish to transfer to another course with us, you may cancel your application and we will refund you any deposits or fees you have paid to us.

Changes to your course after you enrol as a student

We will always try to deliver your course and other services as described. However, sometimes we may have to make changes as set out below:

Changes to option modules

Where your course allows you to choose modules from a range of options, we will review these each year and change them to reflect the expertise of our staff, current trends in research and as a result of student feedback or demand for certain modules. We will always ensure that you have a range of options to choose from and we will let you know in good time the options available for you to choose for the following year.

Major changes

We will only make major changes to the core curriculum of a course or to our services if it is necessary for us to do so and provided such changes are reasonable. A major change in this context is a change that materially changes the services available to you; or the outcomes, or a significant part, of your course, such as the nature of the award or a substantial change to module content, teaching days (part time provision), classes, type of delivery or assessment of the core curriculum.

For example, it may be necessary to make a major change to reflect changes in the law or the requirements of the University’s regulators; to meet the latest requirements of a commissioning or accrediting body; to improve the quality of educational provision; in response to student, examiners’ or other course evaluators’ feedback; and/or to reflect academic or professional changes within subject areas. Major changes may also be necessary because of circumstances outside our reasonable control, such as a key member of staff leaving the University or being unable to teach, where they have a particular specialism that can’t be adequately covered by other members of staff; or due to damage or interruption to buildings, facilities or equipment.

Major changes would usually be made with effect from the next academic year, but this may not always be the case. We will notify you as soon as possible should we need to make a major change and will carry out suitable consultation with affected students. If you reasonably believe that the proposed change will cause you detriment or hardship we will, if appropriate, work with you to try to reduce the adverse effect on you or find an appropriate solution. Where an appropriate solution cannot be found and you contact us in writing before the change takes effect you can cancel your registration and withdraw from the University without liability to the University for future tuition fees. We will provide reasonable support to assist you with transferring to another university if you wish to do so.

Termination of course

In exceptional circumstances, we may, for reasons outside of our control, be forced to discontinue or suspend your course. Where this is the case, a formal exit strategy will be followed and we will notify you as soon as possible about what your options are, which may include transferring to a suitable replacement course for which you are qualified, being provided with individual teaching to complete the award for which you were registered, or claiming an interim award and exiting the University. If you do not wish to take up any of the options that are made available to you, then you can cancel your registration and withdraw from the course without liability to the University for future tuition fees and you will be entitled to a refund of all course fees paid to date. We will provide reasonable support to assist you with transferring to another university if you wish to do so.

When you enrol as a student of the University, your study and time with us will be governed by a framework of regulations, policies and procedures, which form the basis of your agreement with us. These include regulations regarding the assessment of your course, academic integrity, your conduct (including attendance) and disciplinary procedure, fees and finance and compliance with visa requirements (where relevant). It is important that you familiarise yourself with these as you will be asked to agree to abide by them when you join us as a student. You will find a guide to the key terms here, along with the Student Protection Plan, where you will also find links to the full text of each of the regulations, policies and procedures referred to. You should read these carefully before you enrol. Please note that this information is subject to change and you are advised to check our website regularly for any changes before you enrol at the University. A person who is not party to this agreement shall not have any rights under or in connection with it. Only you and the University shall have any right to enforce or rely on the agreement.

The Office for Students (OfS) is the principal regulator for the University.

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