People-Centred Artificial Intelligence (Online) MSc - 2024/5
Awarding body
University of Surrey
Teaching institute
University of Surrey
Framework
FHEQ Levels 6 and 7
Final award and programme/pathway title
MSc People-Centred Artificial Intelligence (Online) (Distance Learning)
Subsidiary award(s)
| Award | Title |
|---|---|
| PGDip | People-Centred Artificial Intelligence (Online) |
| PGCert | People-Centred Artificial Intelligence (Online) |
Modes of study
| Route code | Credits and ECTS Credits | |
| Part-time | PFA61046 | 180 credits and 90 ECTS credits |
QAA Subject benchmark statement (if applicable)
Other internal and / or external reference points
N/A
Faculty and Department / School
Surrey Online - SOL - Computer Science and Elec Eng
Programme Leader
GUILLEMAUT Jean-Yves (CS & EE)
Date of production/revision of spec
20/12/2024
Educational aims of the programme
- The overarching aim of the MSc programme in People-Centred Artificial Intelligence is to provide a high-quality advanced training in a broad range of core AI topics, including machine learning, computer vision and pattern recognition as well as application-specific topics, such as health, the metaverse and sustainability; and important societal, regulatory and legal aspects that will critically inform the future development of AI. The research methods and the project modules will allow students to gain research expertise and explore in more depth a specific area related to AI, allowing them to assist with professional career development within industry or to serve as a precursor to academic research.
- To produce graduates equipped with subject specific knowledge and transferable skills aligned to the Surrey Pillars of graduate attributes and graduates capable of planning and managing their own life-long learning to equip them for roles in industry, in research, in development, in the professions, and/or in public service.
- To provide opportunities for masters students to demonstrate their knowledge, understanding and application of mathematical, scientific, and engineering principles.
- To provide opportunities for masters students to demonstrate their knowledge, understanding and application of engineering concepts and tools in analysis of engineering problems.
- To provide opportunities for masters students to demonstrate their knowledge, understanding and application of design principles in the creation and development of innovative products to meet a defined need.
- To provide opportunities for masters students to demonstrate their knowledge, understanding and application of engineering practice including the importance of project management and communication within an engineering context.
- To provide opportunities for masters students to enhance their global and cultural intelligence through engaging with students from around the world and working on a rich variety of assignments and projects appropriate to their programme.
- To provide opportunities for masters students to enhance their digital capabilities through the use of assignments and projects making various use of programming languages as well as enhancing their general transferable information technology skills in the analysis of data, and via the preparation of assignments and reports.
- To provide opportunities for masters students to enhance their employability skills via use of a training needs analysis which students complete for their project in People-Centred AI to understand how they need to build both their technical and transferable skills.
- To provide opportunities for masters students to enhance their resourcefulness and resilience skills via use of authentic style coursework and assignments, and undertaking a project in People-Centred AI. This will build up a student's personal confidence as they advance from well-structured problems to open-ended problems and an extended project in an area related to People-Centred AI.
- To provide opportunities for masters students to enhance their knowledge and awareness of sustainability via consideration of sustainability issues such as the UN's Sustainability Development Goals appropriate to their programme.
Programme learning outcomes
| Attributes Developed | Awards | Ref. | |
| Apply a comprehensive knowledge of mathematics, statistics, research methods and engineering principles to the solution of complex problems in artificial intelligence. | KC | PGDip, MSc | |
| Formulate and analyse complex problems in artificial intelligence to reach substantiated conclusions. | KC | PGDip, MSc | |
| Select and apply appropriate computational and analytical techniques to model complex problems in artificial intelligence, discussing the limitations of the techniques employed. | KCT | PGDip, MSc | |
| Select and critically evaluate technical literature and other sources of information to solve complex problems in artificial intelligence | CT | PGDip, MSc | |
| Design solutions for complex problems in artificial intelligence that evidence some originality and meet a combination of societal, user, business and customer needs as appropriate to include consideration of applicable health & safety, diversity, inclusion, cultural, societal, environmental and commercial matters, codes of practice and industry standards. | CP | PGDip, MSc | |
| Evaluate the environmental and societal impact of solutions to complex problems in artificial intelligence (to include the entire life-cycle of a product or process) and minimise adverse impacts. | CP | PGDip, MSc | |
| Communicate effectively on complex engineering matters with technical and non-technical audiences, evaluating the effectiveness of the methods used. | PT | MSc | |
| Apply knowledge of mathematics, statistics, research methods and engineering principles to the solution of problems in artificial intelligence. | KC | PGCert | |
| Formulate and analyse problems in artificial intelligence to reach substantiated conclusions. | KC | PGCert | |
| Select and apply appropriate computational and analytical techniques to model problems in artificial intelligence. | KCT | PGCert | |
| Select and evaluate technical literature and other sources of information to solve problems in artificial intelligence. | CT | PGCert | |
| Design solutions for problems in artificial intelligence that evidence some originality and meet a combination of societal, user, business and customer needs as appropriate to include consideration of applicable health & safety, diversity, inclusion, cultural, societal, environmental and commercial matters, codes of practice and industry standards. | CP | PGCert |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Programme structure
Part-time
This Master's Degree programme is studied part-time over two academic years, consisting of 180 credits at FHEQ level 7*. All modules are semester based and worth 15 credits with the exception of project, practice based and dissertation modules.
Possible exit awards include:
- Postgraduate Diploma (120 credits)
- Postgraduate Certificate (60 credits)
*some programmes may contain up to 30 credits at FHEQ level 6.
Programme Adjustments (if applicable)
N/A
Modules
Year 1 (part-time) - FHEQ Level 7
Module Selection for Year 1 (part-time) - FHEQ Level 7
Students are required to undertake the below modules before the dissertation:
Research Methods for People-Centred AI to be taught prior to project in the first year.
The diet represents the modules which will be undertaken throughout the whole course. However, delivery of the module e.g., which order they will be undertaken will be specific depending on which entry point you join. This can be confirmed by contacting your programme lead.
Year 2 (part-time) - FHEQ Level 7
Module Selection for Year 2 (part-time) - FHEQ Level 7
Students are required to undertake the below modules before the dissertation:
Research Methods for People-Centred AI to be taught prior to project in the first year.
The diet represents the modules which will be undertaken throughout the whole course. However, delivery of the module e.g., which order they will be undertaken will be specific depending on which entry point you join. This can be confirmed by contacting your programme lead.
Opportunities for placements / work related learning / collaborative activity
| Associate Tutor(s) / Guest Speakers / Visiting Academics | N | |
| Professional Training Year (PTY) | N | |
| Placement(s) (study or work that are not part of PTY) | N | |
| Clinical Placement(s) (that are not part of the PTY scheme) | N | |
| Study exchange (Level 5) | N | |
| Dual degree | N |
Other information
We are committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This programme is designed to allow students to develop knowledge, skills, and capabilities in the following areas:
Global and Cultural Capabilities:
The online MSc People-Centred AI program fosters global and cultural capabilities by providing an inclusive and diverse learning environment. Students, irrespective of their geographical locations, will collaborate, share perspectives, and engage in cross-cultural discussions through virtual forums and collaborative activities. This global exchange of ideas enriches their understanding of AI's applications and challenges from various cultural viewpoints.
Digital Capabilities:
Being at the forefront of AI education, our program inherently enhances students' digital capabilities. From leveraging advanced AI tools and technologies to navigating online learning platforms seamlessly, students will develop strong digital acumen. The program's structure emphasises hands-on experiences with digital tools, ensuring that students are not just consumers of technology but adept creators and innovators in the digital realm.
Employability:
At the core of our program is a commitment to enhancing students' employability. The curriculum, aligned with industry demands, incorporates real-world applications, and practical projects. The emphasis on practical machine learning skills, business elements, and legal aspects ensures that graduates are well-equipped to meet the diverse demands of the AI job market, making them highly employable professionals.
Resourcefulness and Resilience:
The online format itself fosters resourcefulness and resilience in students. Navigating the digital learning landscape, engaging with asynchronous and synchronous components, and adapting to diverse learning resources instil a sense of resourcefulness. Additionally, the program's emphasis on problem-solving and exposure to cutting-edge AI research nurtures resilience, preparing students for the challenges and uncertainties in the AI field.
Sustainability:
Our commitment to sustainability is reflected in the inclusion of the module "AI and Sustainability". This module addresses the critical intersection of AI technology and environmental considerations. Students will explore how AI can contribute to sustainable practices and gain insights into the ethical dimensions of implementing AI solutions. The emphasis on sustainability themes ensures that graduates are equipped to consider ecological and ethical aspects in their AI endeavours.
Quality assurance
The Regulations and Codes of Practice for taught programmes can be found at:
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.