2021/22 Taught Postgraduate Programme Catalogue
PGCert Artificial Intelligence (online)
|Programme code:||PGC-AI-OD||UCAS code:|
|Duration:||8 Months||Method of Attendance:||Part Time|
|Programme manager:||Prof. Eric Atwell||Contact address:||firstname.lastname@example.org|
Total credits: 60
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
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.
Year1 - View timetable
You will be required to achieve 60 credits for the award of Postgraduate Certificate.
You will be required to study one Compulsory module for 15 credits
|OCOM5100M||Programming for Data Science|
Pre-requisite for: OCOM5200M, OCOM5201M, OCOM5203M, OCOM5204M, OCOM5205M
|15 credits||1 Sep to 31 Oct, 1 Mar to 30 Apr (2mth)(adv yr), 1 Sep to 31 Oct (adv yr)|
You will be required to study 45 credits of Optional modules. One of your Optional modules must be EITHER OCOM5101M Data Science OR OCOM5102M Algorithms
Students are permitted to choose a maximum of 15 credits from this subset
|OCOM5101M||Data Science||15 credits||1 May to 30 Jun (2mth)(adv yr), 1 May to 30 June, 1 Nov to 31 Dec, 1 Nov to 31 Dec (2mth)(adv yr)|
|OCOM5102M||Algorithms||15 credits||1 Jul to 31 Aug, 1 Jan to 28 Feb (adv year)|
Students are required to choose a minimum of 30, maximum of 30 credits from this subset
|OCOM5200M||Machine Learning||15 credits||1 Sep to 31 Oct (adv yr)|
|OCOM5201M||Knowledge Representation and Reasoning||15 credits||1 May to 30 Jun (2mth)(adv yr), 1 May to 30 June|
|OCOM5203M||Deep Learning||15 credits||1 Nov to 31 Dec (2mth)(adv yr)|
|OCOM5204M||Data Mining and Text Analytics||15 credits||1 Jan to 28 Feb (adv year)|
Year2 - View timetable
Last updated: 22/11/2021 16:55:45
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD