MSc Artificial Intelligence Programme Specification 2024-25

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1	ACADEMIC QUALITY TEAM
2	Programme Specifications 2024-25
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5	Programme Title			MSc Artificial Intelligence
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7	This document applies to students who commenced the programme(s) in:			September 2024		Award type			MSc
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9	What level is this qualification?			7		Length of programme			1 year
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11	Mode of study (Full / Part Time)			Full-time
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13	Will the programme use standard University semester dates?			Yes		For York Online programmes, will standard dates for such programmes be used?			N/A.
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15	Awarding institution			University of York		Board of Studies for the programme			Computer Science
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17	Lead department			Computer Science		Other contributing departments
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19	Language of study and assessment			English		Language(s) of assessment			English
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21	Is this a campus-based or online programme?			Campus
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23	Partner organisations
24	If there are any partner organisations involved in the delivery of the programme, please outline the nature of their involvement. You may wish to refer to the Policy on Collaborative Provision
25	N/A.
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27	Reference points
28	Please state relevant reference points consulted in the design of this programme (for example, relevant documentation setting out PSRB requirements; the University's Frameworks for Programme Design (UG or PGT); QAA Subject Benchmark Statements; QAA Qualifications and Credit Frameworks).
29	The MSc. AI meets all of the requirements for the Taught Postgraduate Modular Scheme: Framework for Programme Design, including following one of the recommended layouts of modules and Capstone Project Module. The MSc. AI is informed by QAA Subject knowledge and skills requirements, Subject specific skills requirements, General transferable skills requirements and ACM guidelines.
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32	Credit Transfer and Recognition of Prior Learning
33	Will this programme involve any exemptions from the University Policy and Procedures on Credit Transfer and the Recognition of Prior Learning? If so, please specify and give a rationale
34	No.
35	No.
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37	Exceptions to Regulations
38	Please detail any exceptions to University Award Regulations and Frameworks that need to be approved (or are already approved) for this programme. This should include any that have been approved for related programmes and should be extended to this programme.
39	None.
40	None.
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42	Internal Transfers
43	Please use the boxes below to specify if transfers into / out of the programme from / to other programmes within the University are possible by indicating yes or no and listing any restrictions. These boxes can also be used to highlight any common transfer routes which it would be useful for students to know.
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45		Transfers in:	yes			Transfers out:	yes
46			yes				yes
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48	Statement of Purpose
49	Please briefly outline the overall aims of the programme. This should clarify to a prospective student why they should choose this programme, what it will provide to them and what benefits they will gain from completing it.
50	The MSc in Artificial Intelligence provides advanced study for graduates in Computer Science-related disciplines covering the full breadth of the design, implementation and evaluation of intelligent systems. The programme equips graduates to become leaders in their career field, whether through the deployment of intelligent systems in an industrial setting or cutting-edge research and development, while gaining an understanding of the implications of their work for society as a whole. The programme will build on a solid foundation in the principles and practices of Computer Science, including coding, mathematics and engineering. You will study both the underlying theory and practical skills used in both symbolic and learning-based AI methodologies. You will study, investigate and ultimately understand how these modern AI techniques can be applied in a trustworthy manner to areas such as computer vision, robotics, graphics, analysis of data and games. You will also develop broader skills to enhance your computational thinking and your skills as an engineer enabling you to succeed in an industrial, academic or research environment. A substantial, focussed project will allow you to develop depth of knowledge in a specific area of AI or machine learning while developing the skills necessary to contribute professionally to solving complex commercial and industrial engineering problems.
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61	If there are additional awards associated with the programme upon which students can register, please specify the Statement of Purpose for that programme. This will be most relevant for PGT programmes with exit awards that are also available as entry points. Use additional rows to include more than one additional award. Do not include years in industry / abroad (for which there are separate boxes).
62	Exit Award Title			Is the exit award also available as an entry point?	Outcomes: what will the student be able to do on exit with this award?			Specify the module diet that the student will need to complete to obtain this exit award
63	Postgraduate Diploma (PG Dip) Artificial Intelligence			Exit award only	Students should meet all the learning outcomes to a lesser extent.			Worth 120 module credits - the module diet can be from any taught modules and can include the Capstone Project Module, but to include modules FOAM together with ROCS &/or PRAD. Alternatively students would be be eligible to be transferred to Computer Systems PG Diploma (see row below).
64	Postgraduate Diploma (PG Dip) Computer Systems			Exit award only	A student graduating with a PG Dip qualification will have made progress on achieving all the PLOs, however clearly not to the extent of students who graduate with a MSc. The project work, in particular, gives students the opportunity to build on the core modules in an focussed way with the support of a supervisor.			Worth 120 module credits - the module diet consists of any 120 module credits from across our on-campus PGT programmes.
65	Postgraduate Certificate (PG Cert) Artificial Intelligence			Exit award only	Students should meet all the learning outcomes to a lesser extent.			Worth 60 module credits - the module diet consists of ROCS or PRAD; plus two other AI taught modules, one of which must be FOAM. This is because AI is specialist programme and the PG Cert should contain at least 40 module credits of core specialist material. Should FOAM NOT be achieved, but the student has acheived 60 credits of taught modules (including ROCS or PRAD), they would be eligible to be transferred to the Advanced Computer Science PG Certificate. Alternatively students would be be eligible to be transferred to Computer Systems PG Certificate (see row below).
66	Postgraduate Certificate (PG Cert) Computer Systems			Exit award only	A student graduating with a PG Cert qualification will have made progress on achieving all the PLOs, however clearly not to the extent of students who graduate with a MSc.			Worth 60 module credits - the module diet consists of any 60 module credits from across our on-campus PGT programmes.
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68	Programme Learning Outcomes
69	What are the programme learning outcomes (PLOs) for the programme? (Normally a minimum of 6, maximum of 8). Taken together, these outcomes should capture the distinctive features of the programme and represent the outcomes that students progressively develop in the programme and achieve at graduation. PLOs should be worded to follow the stem 'Graduates will be able to...'
70	1	Differentiate between the different paradigms of AI, their theoretical underpinnings, relative strengths and weaknesses, and suitability for solving different types of problems. [Computational thinking].
71	2	Adapt to new AI technologies, languages, paradigms, terminologies and models as they become available, being confident to use advanced techniques and tools in their practice. [Adaptability].
72	3	Design and build data-driven intelligent systems, using appropriate techniques to manage large volumes of data, using appropriate techniques for labelled and unlabelled data, while understanding limitations caused by data bias. [Data].
73	4	Engineer solutions in which intelligent systems are used to solve real-world problems at scale, using knowledge and skills across the full breadth and depth of computational, machine learning, and mathematical principles. [Engineering; Breadth and depth].
74	5	Make immediate and effective contributions as part of multidisciplinary teams in industry, consultancy or education, by managing workloads, optimising resources and meeting deadlines, using experiences from team projects. [Team working].
75	6	Operate as responsible AI practitioners, by maintaining awareness of the safety, ethics and security of intelligent systems, how they can impact on society, and by continuing to expand and deepen their knowledge through critical engagement with the discipline. [Professionalism].
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77	Diverse entry routes
78	Detail how you would support students from diverse entry routes to transition into the programme. For example, disciplinary knowledge and conventions of the discipline, language skills, academic and writing skills, lab skills, academic integrity.
79	The programme is designed to allow those with a mix of backgrounds, from recent graduates to experienced practitioners working in industry, to acquire knowledge and skills appropriate for modern AI. The first group of modules (ROCS, & FOAM) will provide students with foundations for AI. A second group (PRAD & PADL ) build on these foundations. The final project will give students an opportunity to integrate all of the preceding material and build on it to develop a significant piece of work aligned to their own thematic interests within artificial intelligence. Throughout the programme, but particularly in PRAD, students will be afforded opportunites to develop and enhance transferable skills such as analysis of others' work in order to achieve defined goals, and presentation of technical material in a variety of ways for a range of audiences. Additionally, students will have access to pre-reading material for preparation for the programme, University Library and Writing Centre and Careers. These courses and services are designed to enhance the students' language and academic writing skills, and to support them in planning their future career.
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86	Inclusion
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88	Please confirm by ticking the box on the right that the design, content and delivery of the programme will support students from all backgrounds to succeed. This refers to the University's duties under the Equality Act 2010. You may wish to refer to the optional Inclusive Learning self-assessment tools to support reflection on this issue.									TRUE
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90	Employability
91	Please give a brief overview - no more than 5 sentences - of how the programmes helps develop students' employability. Your Faculty Employability Manager can help reflection on this issue. This statement will be used by Marketing as the basis for external content with respect to employability.
92	Skills for employability are embedded throughout the programme, with opportunities for students to return to skills throughout the degree. Throughout the programmes, industrial case studies are used, and the students are exposed to managed risks and project management. There are two PLOs that specifically address ‘professionalism’ and ‘teamworking’ that should help prepare students for both interview and the work place.
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109	Description of Structure
110	Provide a BRIEF description of the structure of the first stage (UG) or programme (PGT): this is only necessary if this is not evident from the tables above. For instance, an entry might be 'students choose X modules in Autumn Semester from List A and Y modules from List B'. For York Online programmes using the 'carousel' model, the description should include whether any modules have to be taken in a particular order (e.g. if there is an introductory module and/or any constraints on the timing of option and/or CPM or CPM-related modules).
111	Students take 3 taught modules (worth 60 module credits in total) per Semester. This is comprised of 2 core modules and a choice of one option module in both Semester 1 and 2. In addition to the the taught modules above, students take a core individual project (PRAI) over the Summer Semester.
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113	Part-Time Structure (Normally PGT Only): For part-time variants of programmes, please use the box below to specify which modules will be taken in year 1 and which will be taken in year 2 (and so on if more than 2 years).