PGCert Artificial Intelligence (online)

Programme overview

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.

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.

Students will normally study one module at a time.

Year 1

(online)

[Learning Outcomes, Transferable (Key) Skills, Assessment]
View Timetable

You will be required to achieve 60 credits for the award of Postgraduate Certificate.

Compulsory Modules

You will be required to study one Compulsory module for 15 credits

Code	Title	Credits	Semester	Pass for Progression
OCOM5100M	Programming for Data Science	15	1 Mar to 30 Apr, 1 Sep to 31 Oct	PFP

Optional Modules

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

Code	Title	Credits	Semester	Pass for Progression
OCOM5101M	Data Science	15	1 May to 30 June, 1 Nov to 31 Dec
OCOM5102M	Algorithms	15	1 Jan to 28 Feb, 1 Jul to 31 Aug

Students are required to choose a minimum of 30, maximum of 30 credits from this subset

Code	Title	Credits	Semester	Pass for Progression
OCOM5200M	Machine Learning	15	1 Sep to 31 Oct
OCOM5201M	Knowledge Representation and Reasoning	15	1 May to 30 June
OCOM5203M	Deep Learning	15	1 Nov to 31 Dec
OCOM5204M	Data Mining and Text Analytics	15	1 Jan to 28 Feb

Year 2

(online)

[Learning Outcomes, Transferable (Key) Skills, Assessment]
View Timetable

Last updated: 29/04/2024 16:08:29

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