Introduction

Artificial Intelligence (AI) is changing how we live, work and socialise. This programme will expose you to all aspects of AI, from its fundamentals to cutting edge techniques, enabling you to work in this dynamic, fast-moving field.

The School of Natural and Computing Science, in association with The Data Lab, is offering 9 scholarships to cover the cost of tuition for eligible Scotland-based* students commencing the MSc Artificial Intelligence programme in September 2021. *Find out more about the eligibility criteria...

Study Information

Study Options

Learning Mode
On Campus Learning
Degree Qualification
MSc
Duration
12 months, 15 months or 24 months
Study Mode
Full Time or Part Time
Start Month
September or January
Location of Study
Aberdeen
Subject marketing image

The University of Aberdeen has over 30 years’ experience, and a world-wide reputation in AI-related research, focusing on areas such as machine learning, data science, natural language generation, and multi-agent systems. Spin-out successes include ARRIA NLG, one of the world’s leading natural language generation companies.

This programme covers the theoretical underpinning of a wide variety of AI-related techniques including data and text mining, machine learning (deep learning), reasoning, natural language generation, knowledge representation, and distributed AI systems as well as the technology, techniques, tools, software and methodologies used to apply these underlying theories to real-world problems. Students also learn how to engineer and evaluate AI systems.

Our close industry links mean you will have opportunities to apply your skills through training and networking events and industrial placements organised through organisations such as the Data Lab, Intel AI Academy, IBM, Intelligent Plant, and Aberdeen City Council.

See how the courses are scheduled in our September and January start programmes in this infographic.

Available Programmes of Study

Artificial Intelligence

Qualification Duration Learning Mode Study Mode Start Month Location  
MSc 12 months or 24 months On Campus Learning Full Time or Part Time September Aberdeen View

Programme Information

Semester 1

Semester 1

See how the courses are scheduled in our September and January start programmes in this infographic.


Compulsory Courses
Foundations of AI (CS5060)

15 Credit Points

This course presents the fundamental techniques of Artificial Intelligence, used in system such as Google Maps, Siri, IBM Watson, as well as industrial automation systems, and which are core to emerging products such as self-driving vehicles. This course will equip the student to understand how such AI technologies operate, their implementation details, and how to use them effectively. This course therefore provides the building blocks necessary for understanding and using AI techniques and methodologies.

View detailed information about this course
Machine Learning (CS5062)

15 Credit Points

This course will deliver the most sophisticated Machine Learning methodologies and algorithms which would be illustrated across a wide range of applications including but not limited to images, videos, health, time series data, language processing, etc. This course provides students with the Machine Learning principles for continuing learning and working in the area of Data Science and Artificial Intelligence.

View detailed information about this course
Evaluation of AI Systems (CS5063)

15 Credit Points

Artificial intelligence has helped solve complex practical problems such as driving a car, translating text from/to different languages, understanding and answering questions, and playing games such as chess and Go. This course will provide students of our MSc in AI with knowledge of core evaluation concepts, approaches, tools, techniques and technologies.

View detailed information about this course

Optional Courses

Plus one of the following options:

Applied Artificial Intelligence (CS5079)

15 Credit Points

This course will allow students to use cutting-edge AI technologies to investigate the creation and application of AI systems. Such tools include deep learning libraries and simulation environments.

View detailed information about this course
AI and Data: Ethical and Legal Considerations (PH5065)

15 Credit Points

This course will introduce and investigate a number of legal and ethical issues around the ethics of technology, particularly around the ethics of artificial intelligence. We will address questions such as the moral status of artificial agents; the difference, if any, between human rights and artificial rights, problems of data bias. We will also consider the question of resonsibility in this arena and review regulatory frameworks. This course would be of interest to students from computer science, philosophy, law and health sciences.

View detailed information about this course
Semester 2

Semester 2

See how the courses are scheduled in our September and January start programmes in this infographic.


Compulsory Courses
Data Mining and Visualisation (CS551G)

15 Credit Points

This course aims to make students familiar with basic data mining and visualisation techniques and software tools. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time series analysis, and many other techniques. This course will also cover text mining and qualitative modelling. Through this course students will be able to analyse real-world datasets in various domains and discover novel patterns from them. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.

View detailed information about this course
Natural Language Generation (CS551H)

15 Credit Points

The aim of the course is to introduce students who have some background in computing to (1) the varied aims for which Natural Language Generation (NLG) is pursued, (2) the main rule based and statistical methods that are used in NLG, and (3) some of the main NLG algorithms and systems. The course will cover NLG both as a theoretical enterprise (e.g., for constructing models of language production) and as practical language engineering, paying particular attention to the link between NLG and data science. Some programming experience is expected.

View detailed information about this course
Knowledge Representation and Reasoning (CS551J)

15 Credit Points

Recent advances in AI have changed the perception of what machines can do, from on-line search to answering questions. An underlying feature of many AI systems concern how knowledge is acquired, represented, and reasoned with. Companies such as Google, IBM, and Facebook have been developing sophisticated tools for knowledge representation and reasoning. This module provides the theory and practice of knowledge representation and reasoning, also presenting cutting-edge technologies, libraries and tools. At the end of the course students will be able to design, implement and evaluate knowledge-intensive AI systems.

View detailed information about this course
Software Agents and Multi - Agent Systems (CS551K)

15 Credit Points

The global autonomous systems market is expected to be valued at over £13 billion by 2025, involving both software systems and robots. Such autonomous systems act to achieve goals with no human intervention, and are already found in Tesla's self-driving cars, NASA space probes and systems such as Amazon's Echo. This course provides the student with a solid grounding in the theory and tools which underpin such systems, teaching them both how to develop such systems, and use them effectively as part of a larger product.

View detailed information about this course
Semester 3

Semester 3

See how the courses are scheduled in our September and January start programmes in this infographic.


Compulsory Courses
MSc Project in Artificial Intelligence (CS5917)

60 Credit Points

This course will provide students of our MSc in AI programme with the opportunity to develop their own AI research project, under the supervision of a member of staff. Typical projects include extending, improving or adapting existing AI theories or techniques to solve different problems, comparing competing techniques or tools to solve a particular problem, and so on. Students will improve their problem-solving and communication skills, as well as broaden, deepen and consolidate knowledge obtained in other components of the degree.

View detailed information about this course

Programme Fees

Fee information
Fee category Cost
EU / International students £23,500
Tuition Fees for 2021/22 Academic Year
Home / RUK £10,200
Tuition Fees for 2021/22 Academic Year
MSc 15 months On Campus Learning Full Time January Aberdeen View

Programme Information

Semester 1

Semester 1

See how the courses are scheduled in our September and January start programmes in this infographic.


Compulsory Courses
Software Agents and Multi - Agent Systems (CS551K)

15 Credit Points

The global autonomous systems market is expected to be valued at over £13 billion by 2025, involving both software systems and robots. Such autonomous systems act to achieve goals with no human intervention, and are already found in Tesla's self-driving cars, NASA space probes and systems such as Amazon's Echo. This course provides the student with a solid grounding in the theory and tools which underpin such systems, teaching them both how to develop such systems, and use them effectively as part of a larger product.

View detailed information about this course
Knowledge Representation and Reasoning (CS551J)

15 Credit Points

Recent advances in AI have changed the perception of what machines can do, from on-line search to answering questions. An underlying feature of many AI systems concern how knowledge is acquired, represented, and reasoned with. Companies such as Google, IBM, and Facebook have been developing sophisticated tools for knowledge representation and reasoning. This module provides the theory and practice of knowledge representation and reasoning, also presenting cutting-edge technologies, libraries and tools. At the end of the course students will be able to design, implement and evaluate knowledge-intensive AI systems.

View detailed information about this course
Data Mining and Visualisation (CS551G)

15 Credit Points

This course aims to make students familiar with basic data mining and visualisation techniques and software tools. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time series analysis, and many other techniques. This course will also cover text mining and qualitative modelling. Through this course students will be able to analyse real-world datasets in various domains and discover novel patterns from them. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.

View detailed information about this course
Natural Language Generation (CS551H)

15 Credit Points

The aim of the course is to introduce students who have some background in computing to (1) the varied aims for which Natural Language Generation (NLG) is pursued, (2) the main rule based and statistical methods that are used in NLG, and (3) some of the main NLG algorithms and systems. The course will cover NLG both as a theoretical enterprise (e.g., for constructing models of language production) and as practical language engineering, paying particular attention to the link between NLG and data science. Some programming experience is expected.

View detailed information about this course
Semester 2

Semester 2

See how the courses are scheduled in our September and January start programmes in this infographic.


Compulsory Courses
Foundations of AI (CS5060)

15 Credit Points

This course presents the fundamental techniques of Artificial Intelligence, used in system such as Google Maps, Siri, IBM Watson, as well as industrial automation systems, and which are core to emerging products such as self-driving vehicles. This course will equip the student to understand how such AI technologies operate, their implementation details, and how to use them effectively. This course therefore provides the building blocks necessary for understanding and using AI techniques and methodologies.

View detailed information about this course
Evaluation of AI Systems (CS5063)

15 Credit Points

Artificial intelligence has helped solve complex practical problems such as driving a car, translating text from/to different languages, understanding and answering questions, and playing games such as chess and Go. This course will provide students of our MSc in AI with knowledge of core evaluation concepts, approaches, tools, techniques and technologies.

View detailed information about this course
Machine Learning (CS5062)

15 Credit Points

This course will deliver the most sophisticated Machine Learning methodologies and algorithms which would be illustrated across a wide range of applications including but not limited to images, videos, health, time series data, language processing, etc. This course provides students with the Machine Learning principles for continuing learning and working in the area of Data Science and Artificial Intelligence.

View detailed information about this course

Optional Courses
Applied Artificial Intelligence (CS5079)

15 Credit Points

This course will allow students to use cutting-edge AI technologies to investigate the creation and application of AI systems. Such tools include deep learning libraries and simulation environments.

View detailed information about this course
AI and Data: Ethical and Legal Considerations (PH5065)

15 Credit Points

This course will introduce and investigate a number of legal and ethical issues around the ethics of technology, particularly around the ethics of artificial intelligence. We will address questions such as the moral status of artificial agents; the difference, if any, between human rights and artificial rights, problems of data bias. We will also consider the question of resonsibility in this arena and review regulatory frameworks. This course would be of interest to students from computer science, philosophy, law and health sciences.

View detailed information about this course
Semester 3

Semester 3

See how the courses are scheduled in our September and January start programmes in this infographic.


Compulsory Courses
MSc Project in Artificial Intelligence (CS5917)

60 Credit Points

This course will provide students of our MSc in AI programme with the opportunity to develop their own AI research project, under the supervision of a member of staff. Typical projects include extending, improving or adapting existing AI theories or techniques to solve different problems, comparing competing techniques or tools to solve a particular problem, and so on. Students will improve their problem-solving and communication skills, as well as broaden, deepen and consolidate knowledge obtained in other components of the degree.

View detailed information about this course

Programme Fees

Fee information
Fee category Cost
EU / International students £23,500
Tuition Fees for 2021/22 Academic Year
Home / RUK £10,200
Tuition Fees for 2021/22 Academic Year

We will endeavour to make all course options available; however, these may be subject to timetabling and other constraints. Please see our InfoHub pages for further information.

How You'll Study

Learning Methods

  • Group Projects
  • Individual Projects
  • Lectures
  • Peer Learning
  • Research
  • Tutorials
  • Workshops

Why Study Artificial Intelligence?

The University of Aberdeen has a strong history and worldwide reputation in computing science, in particular around Data Science, Natural Language Generation and Artificial Intelligence.

Home to the research success of ARRIA NLG, the University has been ahead of the game in computing science research and teaching for years. Find out more about this hugely successful spin-out company and how it impacts on Artificial Intelligence -

http://blog.arria.com

Entry Requirements

Qualifications

The information below is provided as a guide only and does not guarantee entry to the University of Aberdeen.

Our minimum entry requirement for this programme is a Computing Science degree at 2:2 (lower second class) UK Honours level (or an Honours degree from a non-UK institution which is judged by the University to be of equivalent worth).

Key subjects you must have covered: Python, Algorithmic problem solving and Data Structures. Programming experience in other languages, such as Java, C and C++, is recommended - but not required - to follow the courses taught in this programme.

Applicants with a 2:2 or equivalent in Engineering (e.g. Electronic/Electrical Engineering) will be reviewed by the selectors for suitability on a case-by-case basis.

Please enter your country to view country-specific entry requirements.

English Language Requirements

To study for a Postgraduate Taught degree at the University of Aberdeen it is essential that you can speak, understand, read, and write English fluently. The minimum requirements for this degree are as follows:

IELTS Academic:

OVERALL - 6.5 with: Listening - 5.5; Reading - 5.5; Speaking - 5.5; Writing - 6.0

TOEFL iBT:

OVERALL - 90 with: Listening - 17; Reading - 18; Speaking - 20; Writing - 21

PTE Academic:

OVERALL - 62 with: Listening - 59; Reading - 59; Speaking - 59; Writing - 59

Cambridge English B2 First, C1 Advanced, C2 Proficiency:

OVERALL - 176 with: Listening - 162; Reading - 162; Speaking - 162; Writing - 169

Read more about specific English Language requirements here.

Document Requirements

You will be required to supply the following documentation with your application as proof you meet the entry requirements of this degree programme. If you have not yet completed your current programme of study, then you can still apply and you can provide your Degree Certificate at a later date.

CV
an up-to-date CV/Resumé
Degree Certificate
a degree certificate showing your qualifications
Degree Transcript
a full transcript showing all the subjects you studied and the marks you have achieved in your degree(s) (original & official English translation)
Personal Statement
a detailed personal statement explaining your motivation for this particular programme

Fee Information

Additional Fee Information

  • Fees for individual programmes can be viewed in the Programmes section above.
  • In exceptional circumstances there may be additional fees associated with specialist courses, for example field trips. Any additional fees for a course can be found in our Catalogue of Courses.
  • For more information about tuition fees for this programme, including payment plans and our refund policy, please visit our InfoHub Tuition Fees page.

Funding Opportunities

The School of Natural and Computing Science, in association with The Data Lab, is offering 8 scholarships to cover the cost of tuition for Scottish and EU students commencing the MSc Artificial Intelligence programme in September 2020. Find out more...

Scholarships

Eligible self-funded international Masters students will receive the Aberdeen Global Scholarship. Visit our Funding Database to find out more and see our full range of scholarships.

Aberdeen Global Scholarship (EU)

The Aberdeen Global Scholarship is open to European Union (EU) students.

This is a £2,000 tuition fee discount available to eligible self-funded Postgraduate Masters students who are classed as International fee status and are domiciled in the EU, plus another £3,000 discount for eligible Postgraduate Masters students who would have previously been eligible for Home fees (Scottish/EU) fee status.

View Aberdeen Global Scholarship

Careers

There are many opportunities at the University of Aberdeen to develop your knowledge, gain experience and build a competitive set of skills to enhance your employability. This is essential for your future career success. The Careers and Employability Service can help you to plan your career and support your choices throughout your time with us, from first to final year – and beyond.

What our Alumni Say

Swarada Adavadkar

Swarada Adavadkar

Swarada Adavadkar

Job Details
Data Science Specialist, James Fisher Asset Information Systems
Graduated 2019

Other than technical skills, the degree programme has also helped me in developing my critical thinking and problem-solving skills. The degree programme also gave me an opportunity to develop a self-motivated and analytical approach towards the project work. I would also like to mention that the invaluable guidance on the fundamentals and project work, provided by the professors with strong academic profiles, has definitely contributed to shaping my career.

Our Experts

Head of Discipline
Professor Nir Oren
Other Experts
Dr Nigel Beacham
Dr Wamberto Vasconcelos
Programme Coordinator
Dr Georgios Leontidis

Information About Staff Changes

You will be taught by a range of experts including professors, lecturers, teaching fellows and postgraduate tutors. Staff changes will occur from time to time; please see our InfoHub pages for further information.

Get in Touch

Contact Details

Address
Student Recruitment & Admissions Service
University of Aberdeen
University Office
Regent Walk
Aberdeen
AB24 3FX