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Applied Artificial Intelligence MSc

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Start Dates

22 September 2025, 12 January 2026, 18 May 2026

Duration

1 years full-time


Recent Awards For Excellence

Computer Science & Information Systems - QS 2025
Find out more about these awards
About this course

Overview

Why choose Huddersfield for this course?

  • Open to any discipline - gain applied AI and strategic management skills in one conversion programme.
  • Master machine-learning, robotics and autonomous systems to lead AI-driven change in organisations.
  • Learn from research-active experts shaping smart cities, transport and AI futures.

Accreditation and Professional Links

Recognised connections to give you an extra edge when you graduate. Read More

In 2024, Artificial Intelligence (AI) adoption surged to 72% among organisations, a significant rise from previous years*. For those eager to learn the foundations and stay ahead in this dynamic field, the University of Huddersfield’s Applied Artificial Intelligence MSc offers an ideal opportunity.

Why Study Applied Artificial Intelligence MSc at Huddersfield?

Open to graduates of any discipline, this conversion course uniquely offers you the opportunity to learn both applied technical skills and strategic management, preparing you for roles that manage data and oversee strategic change in organisations as they adopt AI.

This is the first AI Master's programme in the UK that the Chartered Management Institute (CMI) has dual accredited, allowing you to earn a CMI Level 7 Award in Strategic Management and Leadership Practice.

The course aims to equip you with an understanding of data-driven approaches to implementing intelligent behaviour in machines. You’ll develop your knowledge and skills in:

  • Machine learning

  • Robotics

  • Autonomous intelligent systems

  • Data mining

  • Strategic management of data

  • Change and project management

You’ll also learn to critically evaluate existing and emerging Artificial Intelligence technology.

You’ll be taught by international experts in the field of AI. Our academic staff are active in exciting and pioneering research, applying AI methods to address societal changes in healthcare, transportation, smart cities and supply chains. Our research expertise spans the whole spectrum of modern AI, from automated planning and knowledge representation and reasoning, to statistical and data-driven AI, machine learning, deep learning and generative AI.

*www.mckinsey.com

Career opportunities after the course *

Data Scientist

Machine Learning Engineer

Data Engineer

Software Engineer

Data Analyst

*Lightcast

Who can apply?

Entry Requirements

Entry requirements for this course are normally:

  • A BSc, BEng or BA Honours degree (2:2 or above) or equivalent professional qualification in any subject.
  • Other appropriate professional qualifications and/or experience will be considered on an individual basis.

If your first language is not English, you will need to meet the minimum requirements of an English Language qualification. The minimum of IELTS 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 International Entry Requirements page. If you have alternative qualifications or do not meet the IELTS requirement we also offer a range of Pre-Sessional English Programmes.

What will you learn?

Course Details

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 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 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.

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.

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.

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.

This module aims to cover planning for different types of change – discontinuous, radical, incremental or continuous, focusing on both the human and organisational impacts of these changes. As a manager it’s important for you to be able to incorporate management theory and concepts within your working practice. This module aims to help you understand how planning and project management provide opportunities for you to manage change more effectively and efficiently. You’ll have the opportunity to study project management methods, tools and techniques as well as developing an understanding of risk.

Organisational leadership requires the support of strategic information to make decisions that align with institutional objectives. In this module you will critically explore and evaluate the leadership opportunities presented by access to strategic information within an organisation. You will study a range of approaches to managing strategic information at scale, and you will develop knowledge that demonstrates your critical understanding of the impact of both traditional and emerging approaches and issues to managing strategic information.

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.

Teaching and Assessment

Discover what to expect from your tutor contact time, assessment methods, and feedback process.

Where could this lead you?

Your Career

The top five job titles advertised in the UK for graduate roles associated with Artificial Intelligence MSc courses are: Data Scientist; Machine Learning Engineer; Data Engineer; Software Engineer; and Data Analyst.

Source: LightcastTM data - job postings from December 2023 to December 2024 showing jobs advertised associated with a selection of relevant graduate roles.

498.0%
Percentage of the University's postgraduate students go on to work and/or further study within fifteen months of graduating.

* HESA Graduate Outcomes 2022/23, UK domiciled.

£38.5k
The average salary of our postgraduates fifteen months after graduating.

* HESA Graduate Outcomes 2022/23, mean salary, UK domiciled, full-time UK employment as main activity.

The quality of teaching on the AI Master's course at Huddersfield was notably high. What stood out for me was not just the academic rigour, but also the amicable nature of the teaching staff.

- Fuzhan Rahmanian
Artificial Intelligence MSc Graduate

How much will it cost?

Fees and Finance

£9,900 per year

This information is for Home students applying to study at the University of Huddersfield in the academic year 2025/26.

Please note that tuition fees for subsequent years may rise in line with inflation (RPI-X) and/or Government policy. 

For detailed information please visit https://www.hud.ac.uk/study/fees/

This information is for international students applying to study at the University of Huddersfield in the academic year 2025/26.

Please note that tuition fees for subsequent years may rise in line with inflation (RPI-X) and/or Government policy. 

For detailed information please visit https://www.hud.ac.uk/international/fees-and-funding/

Scholarships and Bursaries

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Tuition Fee Loans

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What’s included in your fee?

We want you to understand exactly what your fees will cover and what additional costs you may need to budget for when you decide to become a student with us.

If you have any questions about Fees and Finance, please email the Student Finance Team.

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Why Hud

Explore the unique opportunities and resources that make our institution a top choice for students seeking a well-rounded and future-focused education.

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Careers support

We know you’re coming to university to study on your chosen subject, meet new people and broaden your horizons. However, we also help you to focus on life after you have graduated to ensure that your hard work pays off and you achieve your ambition.

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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.

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Teaching Excellence

Great teaching is engaging and inspiring — it helps you reach your full potential and prepares you for the future. We don’t just teach well — we excel — and we have the awards and recognition to prove it.

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Inspiring Academics

Our researchers carry out world-leading work that makes a real difference to people’s lives. Staff within the Department of Computer Science may teach you on this course.

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Research Excellence

You’ll be taught by staff who want to support your learning and share the latest knowledge and research.

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Accommodation

Looking for student accommodation? Huddersfield has you covered. HudLets has a variety of accommodation types to choose from, no matter what your preference. HudLets is the University’s approved accommodation service, run by Huddersfield Students’ Union.

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Further Study

Many of our graduates stay at Huddersfield to complete postgraduate research degrees at Masters or PhD level.

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