Programme Specifications
Artificial Intelligence
1 : Awarding Institution / Body
Aberystwyth University
2a : Teaching Institution / University
Aberystwyth University
2b : Work-based learning (where appropriate)
Information provided by Department of Computer Science:
Information provided by Department of Mathematics:
3a : Programme accredited by
Aberystwyth University
3b : Programme approved by
Aberystwyth University
4 : Final Award
Master of Science
5 : Programme title
Artificial Intelligence
6 : UCAS code
G790
7 : QAA Subject Benchmark
Information provided by Department of Computer Science:
Information provided by Department of Mathematics:
8 : Date of publication
Information provided by Department of Computer Science:
September 2023
Information provided by Department of Mathematics:
9 : Educational aims of the programme
Information provided by Department of Computer Science:
The program provides students with an overview of topics and methods in Artificial Intelligence with an emphasis on data analysis on machine learning. It provides them with the required skills to apply those techniques in an informed way in a wide range of different application areas. The wide range of different modules provides not only key technical skills and knowledge but also a significant number of transferable skills which are applicable in different scientific as well as professional contexts.
Information provided by Department of Mathematics:
10 : Intended learning outcomes
Information provided by Department of Computer Science:
Information provided by Department of Mathematics:
10.1 : Knowledge and understanding
Information provided by Department of Computer Science:
A1 Discuss limits of applicability of different AI approaches
A2 Describe and use the basic principles of Artificial Intelligence and Machine Learning
A3 Decide if Computational Intelligence methods should be applied and explain advantages and disadvantages of different approaches
A4 Show an appreciation of the issues involved in managing long-term projects
Learning and Teaching
The learning outcomes are covered in a range of different modules as detailed in the table that maps learning outcomes against modules.
Assessment Strategies and Methods
Assessment combines a range of different methods to emphasize the practical aspects of the different learning outcomes. Assessment methods include a presentation, an essay, reports about statistical analyses and an exam.
Information provided by Department of Mathematics:
10.2 : Skills and other attributes
Information provided by Department of Computer Science:
10.2.1 Intellectual Skills
By the end of their programme, all students are expected to be able to demonstrate:
B1 Demonstrate capability to write and present detailed analysis of applications of machine learning
B2 Interpret and report the results of data analysis effectively
B3 Carry out a research proposal competently and efficiently undertake an in-depth literature review
B4 Evaluate the applicability of different technical data management strategies for a variety of applications
B5 Show proficiency in analyzing data sets using appropriate tools
Learning and Teaching
The learning outcomes are covered in a range of different modules as detailed in the table that maps learning outcomes against modules.
Assessment Strategies and Methods
Assessment aims at putting the practical aspects of the different skills at the forefront. Assessment methods include presentations and reports/essays, as well as written examination.
10.2.2 Professional practical skills / Discipline Specific Skills
By the end of their programme, all students are expected to be able to demonstrate:
C1 Describe and use the basic principles of Artificial Intelligence and Machine Learning
C2 Practically apply Artificial Intelligence and Machine Learning principles
C3 Decide if Computational Intelligence methods should be applied and explain advantages and disadvantages of different approaches
C4 Demonstrate skills in designing, running, and documenting experiments using machine learning
C5 Demonstrate capability to write and present detailed analysis of applications of machine learning
Learning and Teaching
The learning outcomes are covered in a range of different modules as detailed in the table that maps learning outcomes against modules.
Assessment Strategies and Methods
The assessment methods bring students in contact with current research literature in the area and help them developing the different skills by including presentations, and essay writing.
Information provided by Department of Mathematics:
10.3 : Transferable/Key skills
Information provided by Department of Computer Science:
By the end of their programme, all students are expected to be able to:
D1 Work as part of a team
D2 Present the material they have learned in an informed, clear manner
D3 Demonstrate a range of bibliographic and computing skills
D4 Write a suitable research proposal
Learning and Teaching
The learning outcomes are covered in a range of different modules as detailed in the table that maps learning outcomes against modules.
Assessment Strategies and Methods
Assessment includes presentations, essay and report writing, both including a significant literature review.
Information provided by Department of Mathematics:
11 : Program Structures and requirements, levels, modules, credits and awards
MSC Artificial Intelligence [G790]
Academic Year: 2023/2024 scheme - available from 2019/2020
Duration (studying Full-Time): 1 years12 : Support for students and their learning
Every student is allocated a Personal Tutor. Personal Tutors have an
important role within the overall framework for supporting students and
their personal development at the University. The role is crucial in
helping students to identify where they might find support, how and where
to seek advice and how to approach support to maximise their student
experience. Further support for students and their learning is provided by
Information Services and Student Support and Careers Services.
13 : Entry Requirements
Details of entry requirements for the scheme can be found at http://courses.aber.ac.uk
14 : Methods for evaluating and improving the quality and standards of teaching and learning
All taught study schemes are subject to annual monitoring and periodic
review, which provide the University with assurance that schemes are
meeting their aims, and also identify areas of good practice and
disseminate this information in order to enhance the provision.
15 : Regulation of Assessment
Academic Regulations are published as Appendix 2 of the Academic Quality
Handbook: https://www.aber.ac.uk/en/aqro/handbook/app-2/.
15.1 : External Examiners
External Examiners fulfill an essential part of the University’s Quality
Assurance. Annual reports by External Examiners are considered by
Faculties and Academic Board at university level.
16 : Indicators of quality and standards
The Department Quality Audit questionnaire serves as a checklist about the
current requirements of the University’s Academic Quality Handbook. The
periodic Department Reviews provide an opportunity to evaluate the
effectiveness of quality assurance processes and for the University to
assure itself that management of quality and standards which are the
responsibility of the University as a whole are being delivered
successfully.