Artificial Intelligence

Artificial Intelligence at the University of St Andrews offers a comprehensive curriculum designed to equip students with a solid foundation in both the theoretical and practical aspects of AI. This programme explores the key areas of machine learning, data analysis, robotics, natural language processing, and computer vision, emphasizing the development of innovative solutions to real-world problems. Students will engage with cutting-edge topics such as deep learning, neural networks, and intelligent systems, gaining the necessary skills to design, implement, and evaluate AI applications across various industries.

The programme is structured to combine rigorous theoretical coursework with practical projects, enabling students to apply their knowledge in laboratory settings and collaborative research initiatives. Throughout the programme, students will learn programming languages commonly used in AI development, such as Python, and acquire skills in algorithm design, data structures, and software engineering. Additionally, they will explore ethical issues related to AI, including bias, privacy, and societal impacts, preparing them to develop responsible and sustainable AI solutions.

Classes are delivered by expert faculty members with extensive research backgrounds in artificial intelligence, ensuring that students are exposed to the latest advancements and industry practices. The programme also offers opportunities for internships and industry collaborations, connecting students with leading tech companies and innovation hubs.

Graduates of this programme will be well-prepared for a wide range of careers in AI research, software development, data science, automation, and beyond. They will possess the technical expertise and critical thinking skills necessary to lead the development of intelligent systems and contribute to technological innovation in a variety of sectors globally. Whether pursuing further academic research or entering the workforce directly, students will find themselves equipped with a thoroughly-rounded education that combines theoretical understanding with practical implementation, making them highly desirable in the rapidly evolving field of artificial intelligence.

The taught portion of the MSc programme includes eight modules: five compulsory and three optional from a wide range available. Teaching methods include lectures, seminars, tutorials and practical classes. Most modules are assessed through practical coursework exercises and examinations. Class sizes typically range from 10 to 50 students. 

All students are assigned an advisor who meets with them at the start of the year to discuss module choices and is available to assist with any academic difficulties during the year. A designated member of staff provides close supervision for the MSc project and dissertation.

Compulsory modules

• Masters Core Skills: equips students with essential skills in a range of topics including technical writing for computer science and information technology, presentation skills, research skills and project planning, all reinforced by practical assignments. 
• Object-Oriented Modelling, Design and Programming: introduces and reinforces object-oriented modelling, design and implementation to provide a common basis of skills, allowing students to complete programming assignments within other MSc modules.
• Artificial Intelligence Principles: foundational knowledge of artificial intelligence (AI) with an overview of AI and its philosophy.
• Artificial Intelligence Practice: practical design and implementation of artificial intelligence (AI), covering techniques in the areas of AI reasoning, planning, doing and learning. 

And one or both of:

• Language and Computation: covers the major aspects of natural language processing and speech understanding.
• Constraint Programming: introduces constraint-based reasoning as a powerful mechanism for knowledge representation and inference.

Optional modules

• Masters Programming Projects
• Software Engineering Principles
• Software Engineering Practice
• Critical Systems Engineering
• Software Architecture
• Human Computer Interaction Principles and Methods
• Interactive Software and Hardware
• User-Centred Interaction Design
• Information Visualisation and Visual Analytics
• Large-Scale Systems
• Database Management Systems
• Web Technologies
• Information Security Management
• Green Information Technology
• Information Technology Projects
• Knowledge Discovery and Datamining

Additional optional modules

• Computer Graphics
• Distributed Systems
• Programming Language Design and Implementation
• Computer Architecture
• Computer Security
• Concurrency and Multi-Core Architectures
• Multimedia
• Video Games

Dissertation

During the second semester, students work with staff to define and agree upon a topic for the extended project, which they will work on during the final three months of the course, and which culminates in a 15,000-word dissertation. Dissertation projects may be group-based or completed individually (students are assessed individually in either case).

The dissertation typically comprises: a review of related work; the extension of existing or the development of new ideas; software implementation and testing; analysis and evaluation. Students are required to give a presentation of their work in addition to the written dissertation.

Each project is supervised by one or two members of staff, typically through regular meetings and reviews of software and dissertation drafts.

If students choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma instead, finishing the course at the end of the second semester of study.

Requirements

• Postgraduate candidates will be expected to hold a Russian Bachelor’s degree - Diplom Bakalavra/ Bakalavr Diploma or a Specialist Degree issued by the Russian Federation -  Specialist Diploma / Diplom Specialista.  In either case, students should have completed their degree with an average mark (grade) of 4 or higher on the Russian 5-point marking scale.  Students with higher level qualifications such as Magistr, the Kandidat Nauk, would also be considered for postgraduate study.
• CV
• Letter of intent (300 to 500 words)
• Two original signed academic references
• Academic transcripts and degree certificates 
• IELTS 7.0

Want to improve your English level for admission?

Prepare for the program requirements with English Online by the British Council.

• ✔️ Flexible study schedule
• ✔️ Experienced teachers
• ✔️ Certificate upon completion

📘 Recommended for students with an IELTS level of 6.0 or below.

Enroll in the course

Scholarships

• Russia Global Education Program (GEP)
• Accommodation Award
• Chevening Scholarships 
• Thomas and Margaret Roddan Trust Bursary 

Artificial Intelligence at the University of St Andrews offers a comprehensive exploration of the core principles, techniques, and applications of AI. This program is designed to equip students with a solid foundation in computer science, programming, and machine learning, alongside specialized knowledge in artificial intelligence algorithms, data structures, and neural networks. The curriculum typically encompasses modules on robotics, natural language processing, computer vision, and autonomous systems, providing a well-rounded understanding of how AI technologies are developed and deployed across various industries. Students engage in practical projects that involve coding, problem-solving, and the use of AI frameworks, fostering both theoretical understanding and hands-on skills. The program emphasizes the ethical considerations and societal impacts of AI, encouraging students to think critically about issues such as bias, privacy, and the future of work. Throughout their studies, students are supported by expert faculty with research interests spanning multiple AI disciplines. The program often includes opportunities for collaboration with external partners, internships, and involvement in cutting-edge research initiatives. Graduates of the course are prepared for careers in AI research, software development, data analysis, and technological innovation, or to pursue further postgraduate study. The program is tailored to meet the evolving demands of the AI industry, ensuring that students graduate with relevant, up-to-date knowledge and skills to excel in this dynamic field.