The MSc Artificial Intelligence at the University of Aberdeen provides comprehensive training in both the foundations and cutting-edge developments of AI. You'll study topics such as machine learning, natural language generation, data mining, and distributed systems, while gaining hands-on experience with real-world tools and technologies. The programme also explores the legal and ethical dimensions of AI and includes a research project, often in collaboration with industry. With over 30 years of AI research expertise and strong industry ties including spin-outs like ARRIA NLG you’ll be well-prepared for careers in this fast-moving field.
At a glance
What You'll Study
- Stage 1
-
Symbolic AI (CS502K) 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.
Machine Learning (CS5062) 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.
Evaluation of AI Systems (CS5063) One of the biggest challenges in Artificial Intelligence is evaluating how well AI systems work. This course will provide students of our MSc in AI with knowledge of core evaluation concepts, approaches, tools, techniques and technologies; we will also look at software testing of AI systems.
View detailed information about the Evaluation of AI Systems course
Applied Artificial Intelligence (CS5079) 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 the Applied Artificial Intelligence course
- Stage 2
-
Knowledge Representation and Reasoning (CS551J) 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 the Knowledge Representation and Reasoning course
Software Agents and Multi-Agent Systems (CS551K) 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 the Software Agents and Multi-Agent Systems course
Data Mining with Deep Learning (CS552J) 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 the Data Mining with Deep Learning course
Natural Language Generation (CS551H) 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 the Natural Language Generation course
- Stage 3
-
MSc Project in Artificial Intelligence (CS5917) 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 the MSc Project in Artificial Intelligence course
How You'll Study
Course delivery is by means of lectures, seminars and small group tutorials. On specific courses, these will be supplemented by external speakers.
Learning Methods
Assessment Methods
By coursework, written examination, or a combination thereof, as prescribed for each course, and by submission of a dissertation. The degree of MSc shall not be awarded to a candidate who fails to achieve a CGS grade of D3 or above in QI5900, irrespective of their performance in other courses.
Why Study Artificial Intelligence?
- Over 30 years of AI research excellence with a global reputation in areas like machine learning, data science, and natural language generation.
- Covers both core AI theory and the latest technologies, including ethical and practical applications.
- Strong links with companies such as ARRIA NLG, IBM, and Intel, offering opportunities for placements, networking, and real-world projects.
- Taught by active researchers, ensuring content is shaped by the latest developments in the field.
- Final research projects can be industry-led, giving you valuable experience solving real-world problems with AI.
Entry Requirements
- Applicants for admission will normally be expected to hold a relevant Honours degree with a 2:1 standard from a recognised university or body.
- Applicants without this qualification may be admitted subject to having an alternative qualification, or an approved level of work experience appropriate to the field of study. Also taken into careful consideration is the trajectory of results, an applicant without an overall 2.1 but with 2.1 results in their final two years of study may be admitted.
English 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:
- Your first degree was studied in English
OR
- IELTS Academic: OVERALL - 6.5 with: Listening - 5.5; Reading - 6.0; Speaking - 5.5; Writing - 6.0
- TOEFL iBT: OVERALL - 90 with: Listening - 17; Reading - 21; Speaking - 20; Writing - 21
- PTE Academic: OVERALL - 62 with: Listening - 51; Reading - 54; Speaking - 51; Writing - 54
- Cambridge English Advanced & Proficiency: OVERALL - 176 with: Listening - 162; Reading - 169; Speaking - 162; Writing - 169
Fees
- The tuition fee for entry in September is 105,000 QR per year.
- Tuition fees are fixed at the point of entry so there is no annual increase for returning students.
- Flexible payment methods are available.