Everything you need to know...
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What is the fee?
Home: £11,490 for the course
International/EU: £21,735 for the course -
How long will I study?
1 Year
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Where will I study?
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When do I start?
September 2027
January 2028
Course summary
- Develop a deep understanding of artificial intelligence systems.
- Explore generative AI, machine learning and computer vision.
- Understand how to deploy AI solutions based on client needs.
- Identify the ethical and societal impacts of applying AI.
- Collaborate with our industry contacts on live projects.
Our MSc Applied Artificial Intelligence programme develops the multidisciplinary skills to understand what AI solutions are available and how they can be successfully deployed in any discipline. You’ll focus on AI tools and technologies such as ChatGPT, Gemini, Copilot, Azure and Google Colab – preparing to solve problems, provide insights and create system prompts in a wide range of contexts.
Come to an open day
Find out more at our postgraduate open days. Book now for your place.
How you learn
On your MSc Applied Artificial Intelligence programme, you’ll be taught by experienced academics – experts in neural networks, computer vision and large language models. The team have a wealth of practical knowledge in using and applying AI systems in research, academic and industrial contexts. They’re all researchers in various fields of AI – with excellent track records in recognised academic conference publications and journal papers.
The course emphasises the practical skills you’ll need to deploy existing AI systems to solve real-world problems, while also being aware of the ethical and societal implications. Our expert team will help you gain both theoretical knowledge and practical AI skills – enhancing your employability when you graduate.
You’ll also prepare for real-world challenges through practical projects and collaborations with industry partners – such as NHS, South Yorkshire Innovation Program and The Advanced Food Innovation Centre (AFIC). Assessments are based on realistic, problem-based situations, mirroring the challenges you’ll face in your career.
You learn through:
- lectures
- tutorials and seminars
- regular feedback
- laboratory sessions
- real-world problems
- practical activity-based sessions
- group and individual project work
- supervisor support and guidance
- acting as mentors for new students
- self-directed study
What you’ll study on the MSc Applied Artificial Intelligence
You’ll begin the masters in Applied AI by exploring and learning the fundamental principles that underpin AI systems. This includes machine learning, deep learning, data mining, natural language processing, computer vision, and intelligent systems. Through a ‘no-code’ web approach, you’ll explore AI model creators and develop an awareness of available AI systems, which will also help you appreciate how data interacts with AI.
Using the applied AI knowledge you’ve gained, you’ll work with clients on projects to understand how AI can support to meet their business needs. During those projects, you’ll have regular scrum meetings with academics and clients to identify narratives, learning needs and action plans. Through that collaboration and critical evaluation, you’ll deploy an optimal AI solution to meet the real-world needs of the client. For example, you could be deploying Chatbots as first-line triage to support wellbeing, identifying dangerous warehouse environments to improve site health and safety, or implementing trend analysis of transport and footfall data.
Alongside developing your understanding of how to apply AI, you’ll also consider the challenges, requirements and limitations of those AI tools.
Course support
You will be supported in your learning journey towards highly skilled employment through a number of key areas. These include:
- access to specialist support services to help with your personal, academic and career development.
- access to our Skills Centre with one-to-ones, webinars and online resources, where you can get help with planning and structuring your assignments.
- industry-specific employability activities such as live projects and networking opportunities.
Applied learning
Work experience
The course also has a work experience route that offers a placement opportunity in industry of up to 12-months. For further information, please see Applied artificial intelligence (Work Experience).
Apply your AI skills to real world challenges
Our teaching team maintains strong links with the AI industry, making sure your curriculum content is relevant and aligned with industry requirements. We’ve established strong collaborations with local and national research centres and industry partners – such as SHU’s Advanced Wellbeing Research Centre, Sheffield Robotics, the Advanced Manufacturing Research Centre, AstraZeneca, and the British Machine Vision Association. These collaborations with domain experts provide you with insights into cutting-edge technologies and real-world applications.
Our collaborations also provide you with live projects within the course, where you’ll work individually or in groups on real-world AI challenges. These projects encourage creativity, critical thinking and teamwork – mirroring the complexity of scenarios encountered in the professional world.
You’ll be able to delve deeply into a specific area of interest, applying your knowledge to solve complex problems. Supervised by experienced tutors and industry partners, you’ll gain valuable experience in these projects, contributing meaningfully to the field of AI.
Grow your professional network
Throughout the course, you’ll be able to connect with industrial professionals, enhancing your understanding of the AI landscape. These are great chances to open doors to mentorship, internships, and potential employment opportunities.
One of the most important events is our Festival of Artificial Intelligence – an enriching day filled with presentations, networking opportunities, and celebrations of completed projects. The event also includes themed competitions, allowing you to further showcase your skills and knowledge in AI, while promoting innovation and development in this rapidly evolving field.
Course leaders and tutors
Dr Maria Luisa Davila Garcia
Senior LecturerStaff profile for Dr Maria Luisa Davila Garcia, Lecturer in Artificial Intelligence at Sheffield Hallam University.
Modules studied may differ depending on when you start your course.
Modules
Module and assessment information for future years is displayed as currently validated and may be liable to change. When selecting electives, your choices will be subject to the core requirements of the course. As a result, selections may be limited to a choice between one of two or more specified electives in some instances.
Modules studied may differ depending on when you start your course.
Final year
Compulsory modules
This module will solve a problem(s) by applying and developing artificial intelligence techniques and engaging with real-world situations. The module will develop an AI project that will be practical in nature, providing an opportunity to learn from work-related activities and to develop skills for collaborating in groups and with external clients.
You’ll study topics such as:
- Identify, develop, and adapt appropriate tools, techniques, and systems from the AI area
- Write project specification(s) and learn and apply project management skills as part of group work
- Identify project risks and issues that may impact the delivery of the final work
- Testing and evaluation of solutions
- Group working and interpersonal communication techniques
- Evaluation and reflection of personal performance
Learn how to apply Artificial Intelligence tools in a wide range of real-world scenarios, contributing to the solution of a problem or improvement of the processes in the development of the solution. Explore the challenges involved in the correct selection and use of AI tools by understanding the needs of a particular domain. Develop creative and critical thinking skills by apply an existing AI tool efficiently in a wide range of domains.
This module aims to:
Develop the student’s abilities to analyse and explain the applications of artificial intelligence critically.
Provide experience with using, managing and evaluating artificial intelligence resources.
Apply such experience to the support decision about the use and integration of existing AI tools in a variety of areas/domains.
Typically, you will study topics such as:
Explore ‘No-code’ web-based AI model creators.
‘No-code’ system-on-a-chip such as Micro:bit
Exploit large language model-based systems and generative AI
Conversational agents.
How to interact with technical AI teams to develop AI projects
Assess existing models using interpretability tools
Testing, optimisation and evaluation of an AI project
Present and demonstrate an AI project
This module will develop skills to effectively convey intricate artificial intelligence (AI) ideas to diverse audiences. Focused on enhancing presentation skills, the module places a strong emphasis on translating complex concepts into accessible explanations while fostering critical evaluation of peer-reviewed scientific publications.
You’ll study topics such as:
- Independent thought and learner autonomy
- Seminar presentations in the format of the 3MT (three minutes thesis)
- Research-based scientific communication
- Critical evaluation of research findings
- Effective presentations
This module will apply the technical knowledge and understanding developed across the course into an original research project. This will include critical and ethical analysis of literature, synthesising the findings and tailoring them to the specific context of their research projects using a suitable research methodology.
You’ll study topics such as:
- Critical and ethical review of the literature
- Selection and application of appropriate research tools, techniques, or methods
- Design and development of the artefact/prototype
- Testing and user evaluation
- Critical reflection – evaluating the project deliverables and project success/failure
- Legal, social, and ethical considerations in the design and development of computer-based systems
- Sustainable development and deployment
Develop the basic foundations of artificial intelligence tools, including approaches and methods. Explore the influence of the data on AI solutions, the challenges, requirements and limitations of the newest AI tools for main domains. Develop a comprehensive understanding of artificial intelligence principles, theories, and practices through examples from machine learning, deep learning, data mining, natural language processing, computer vision, and intelligent systems.
This module aims to:
Introduce students to the terminology and concepts inherent to artificial intelligence.
Identify the technical requirements and regulations for using and integrating artificial intelligence tools.
Investigate how artificial intelligence transforms industries and creates opportunities while improving processes and outcomes.
Typically, you will study topics such as:
Foundations of AI: key definitions and history.
Machine learning and deep learning: how to use pre-trained models.
Natural Language Processing: how to use high-level interfaces to create conversational AI applications.
Computer Vision: basic concepts behind image recognition and object detection
AI in practice: case studies from business, healthcare, and education.
Ethics, privacy, and regulation: responsible AI use, data protection, governance frameworks.
Future trends in AI: emerging technologies, human-AI collaboration, societal impact.
This module develops skills to design and conduct rigorous research projects in computing.
You’ll study topics such as:
- Identify research problems: Explore current challenges and opportunities in computing to uncover relevant research areas
- Formulate research questions: Craft precise questions, aims, and objectives aligned with identified problems
- Review literature and artifacts: Critically analysing existing research to synthesize knowledge and identify gaps
- Propose research methods: Evaluate and select appropriate research techniques specific to your computing area
- Communicate research proposals: Craft comprehensive proposals that meet professional, legal, and ethical standards
Future careers
This MSc Applied Artificial Intelligence prepares you for a range of careers and industries, including:
- AI development, building and customising new AI systems to solve problems in a wide range of industries.
- data mining analysis, using AI to provide insights into data for organisations
- machine learning engineering, designing new AI systems that can take actions without being directed.
- prompt engineering for large-language-model systems
All in on your career
We promise you’ll be ready to launch your career. With employer connections, hands-on learning and lifelong career support, we’ll help make your ambition a reality.
Equipment and facilities
On this course you’ll work with specialist facilities for research, advanced robotics platforms, computing platforms, and state-of-the-art-machine learning software and application development environments – such as:
- Microsoft Azure Machine Learning
- Amazon SageMaker
- Transformers, API, LLM (Large languages models), agentic models.
- Care-O-bot Social Robot
- NAO
- Pepper
- TurtleBot
- Azure
- Colab
Where will I study?
You study at City Campus through a structured mix of lectures, seminars and practical sessions as well as access to digital and online resources to support your learning.
City Campus
City Campus is located in the heart of Sheffield, within minutes of the train and bus stations.
City Campus map | City Campus tour
Adsetts library
Adsetts Library is located on our City Campus. It's open 24 hours a day, every day.
Explore the libraryEntry requirements
All students
Normally an undergraduate degree at 2:2 or above, in a related field.
If English is not your first language, you will need an IELTS score of 6.0 with a minimum of 5.5 in all skills, or equivalent.
Additional information for EU/International students
If you are an International or non-UK European student, you can find out more about the country specific qualifications we accept on our international qualifications page.
For details of English language entry requirements (IELTS), please see the information for 'All students'.
Fees and funding
Home students
Our tuition fee for UK students starting full-time study in 2027/28 is £11,490 for the course.
If you are studying an undergraduate course, postgraduate pre-registration course or postgraduate research course over more than one academic year then your tuition fees may increase in subsequent years in line with Government regulations or UK Research and Innovation (UKRI) published fees. More information can be found in our terms and conditions under student fees regulations.
International students
Our tuition fee for International/EU students starting full-time study in 2027/28 is £21,735 for the course.
Scholarships and financial support
Find information on scholarships, bursaries and postgraduate student loans.
International scholarships up to £3000 ›
Alumni scholarships up to £2000 ›
Postgraduate loans for UK students ›
Additional course costs
The links below allow you to view estimated general course additional costs, as well as costs associated with key activities on specific courses. These are estimates and are intended only as an indication of potential additional expenses. Actual costs can vary greatly depending on the choices you make during your course.
General course additional costs
Additional costs for School of Computing and Digital Technologies (PDF, 241.2KB)Legal information
Any offer of a place to study is subject to your acceptance of the University’s Terms and Conditions and Student Regulations.
