2021/22 Taught Postgraduate Programme Catalogue
MSc Artificial Intelligence (online)
Programme code: | MSC-AI-OD | UCAS code: | |
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Duration: | 24 Months | Method of Attendance: | Part Time |
Programme manager: | Prof. Eric Atwell | Contact address: | e.s.atwell@leeds.ac.uk |
100% online
Total credits: 180
Entry requirements:
Standard entry will require an honours degree equivalent to a UK first/upper second class, demonstrating aptitude for programming and quantitative reasoning in any mathematical / highly numerate undergraduate degree. Graduates with first degrees from most quantitative subject areas would be eligible, for example: mathematics, computer science, statistics, engineering (any), physics / physical sciences, space science, econometrics, quantitative research methods etc.
Graduates who hold an honours degree equivalent to a UK lower second class from a mathematics based discipline (see examples above) may also be eligible providing they can demonstrate relevant professional experience, a minimum of 3 years in related professional environment.
Graduates who hold an honours degree equivalent to a UK first/upper second class from non-mathematics-based disciplines may also be eligible providing they can demonstrate relevant professional experience, a minimum of 3 years in a related professional environment.
For students whose first language is not English, an English language qualification at a suitable level: IELTS 6.5 or equivalent with no lower than 6.5 in each category.
School/Unit responsible for the parenting of students and programme:
Digital Education Service
Examination board through which the programme will be considered:
Digital Education Service
Relevant QAA Subject Benchmark Groups:
The relevant QAA Benchmark is the Subject Benchmark Statement for a Masters Degree in Computing (2011) - Section 7 of which defines the specific threshold levels. See: https://www.qaa.ac.uk/docs/qaa/subject-benchmark-statements/sbs-masters-degree-computing.pdf
Programme specification:
The programme provides a rigorous training in the foundational ideas and methods that underpin recent progress in the field of Artificial Intelligence.
The programme begins with the development of core skills in programming, needed to build AI systems, and foundational knowledge on algorithms and data science.
Following this, the content is broadly-based, covering both neural networks and symbolic approaches for making sense of sensory data and natural language, and for reasoning about the world.
The central topic of machine learning is covered in depth, including recent developments in deep learning.
There is an emphasis on integrated and unified systems that combine different sensory modalities (e.g. vision, audition), together with factual knowledge and reasoning. Such integration will be essential for many future applications of AI.
Throughout the programme, the material will be brought to life in a variety of applications in areas such as healthcare, finance, and environmental sciences.
Graduates from the MSc will be well positioned to work on the application of AI within the private and public sectors in many domains, including healthcare, finance, retail and government. The programme also provides a grounding for continuing on to study for a PhD in the area of AI.
Year1 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
In your first year you will typically study three Foundation modules, shown below as Compulsory. You will typically study three out of the six Development modules, shown below as Optional.
Compulsory modules:
You will study three Foundation modules as Compulsory
OCOM5100M | Programming for Data Science Pre-requisite for: OCOM5200M, OCOM5201M, OCOM5203M, OCOM5204M, OCOM5205M, OCOM5300M | 15 credits | 1 Sep to 31 Oct (adv yr), 1 Mar to 30 Apr, 1 Mar to 30 Apr (2mth)(adv yr) | |
OCOM5101M | Data Science | 15 credits | 1 Nov to 31 Dec (2mth)(adv yr), 1 May to 30 Jun (2mth)(adv yr), 1 May to 30 June | |
OCOM5102M | Algorithms | 15 credits | 1 Jan to 28 Feb, 1 Jan to 28 Feb (adv year), 1 Jul to 31 Aug |
Optional modules:
You will typically study three out of six Developmental modules as Optional in your first year.
Year2 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
In your second year you will typically study the remaining three out of six Development modules, shown below as Optional. You will typically study the Project module, shown as Compulsory.
Compulsory modules:
The Project module is compulsory for the second year of the programme.
OCOM5300M | Artificial Intelligence Project | 45 credits | 1 Mar to 31 Aug (6mth)(adv yr), 1 Sep to 28 Feb (6mth)(adv yr), 1 Nov to 30 Apr (6mth)(adv yr), 1 Jan to 30 Jun (6mth)(adv yr), 1 May to 31 Oct (6mth)(adv yr) |
Optional modules:
You will study the remaining three Development modules as Optional modules.
Candidates will be required to study 45 credits from the following optional modules:
OCOM5200M | Machine Learning | 15 credits | 1 Sep to 31 Oct (adv yr) | |
OCOM5201M | Knowledge Representation and Reasoning | 15 credits | 1 May to 30 June, 1 May to 30 Jun (2mth)(adv yr) | |
OCOM5202M | Ethics of Artificial Intelligence | 15 credits | 1 Jul to 31 Aug | |
OCOM5203M | Deep Learning | 15 credits | 1 Nov to 31 Dec, 1 Nov to 31 Dec (2mth)(adv yr) | |
OCOM5204M | Data Mining and Text Analytics | 15 credits | 1 Jan to 28 Feb, 1 Jan to 28 Feb (adv year) | |
OCOM5205M | Robotics | 15 credits | 1 Mar to 30 Apr, 1 Mar to 30 Apr (2mth)(adv yr) |
Last updated: 30/06/2021 16:15:39
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