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MSc Artificial Intelligence

Study of the design, implementation and evaluation of intelligent systems.

Year of entry: 2023 (September)

Length

1 year full-time

Start date

September 2023 (semester dates)

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Discover the impact of AI on industry, cutting-edge research and society as a whole.

This course will build on a solid foundation in the principles and practices of computer science, including coding, mathematics and basic engineering. You will study both the underlying theory and practical skills used in symbolic and learning-based AI methodologies. You will see how these modern AI techniques and apply these to areas such as computer vision, robotics, graphics, analysis of data and games.

Teaching

Our staff are at the cutting edge of their fields and we maintain strong links with industry.

Course content

Throughout the year, you will study five core modules and two option modules.

You will also develop skills to enhance your computational thinking engineering to enable you to succeed in an industrial, academic or research environment. The research project allows you to develop knowledge in a specific area of AI or machine learning, while developing skills to contribute professionally to solving commercial and industrial engineering problems.

Modules

Core modules

  • Foundations of Artificial Intelligence and Machine Learning
  • Research Methods for Computer Science
  • Probabilistic and Deep Learning
  • Professional and academic development

Option modules

You will also study two option modules:

  • Autonomous Robotic Systems Engineering
  • Computer Vision and Graphics
  • AI Problem-Solving with Search and Logic
  • Evolutionary and Adaptive Computing

Our modules may change to reflect the latest academic thinking and expertise of our staff.

Research project

  • Individual Capstone Project in AI

Work on your individual project will start around the beginning of April, and you will receive regular one-to-one supervisions throughout your project.

You will continue to work on your individual project over the summer, and there will be continuing supervision and research-group meetings to discuss your project. You will finish the course when you hand in your dissertation and paper for your project in September.

The York approach

Every course at York is built on a distinctive set of learning outcomes. These will give you a clear understanding of what you will be able to accomplish at the end of the course and help you explain what you can offer employers. Our academics identify the knowledge, skills, and experiences you'll need upon graduation and then design the course to get you there.

Students who complete this course will be able to:

Differentiate between the different paradigms of AI, theoretical underpinnings, relative strengths and weaknesses, and suitability for solving different types of problems (computational thinking).

Adapt to new AI technologies, languages, paradigms, terminologies and models as they become available, being confident to use advanced techniques and tools in practice
(adaptability).

Design and build data-driven intelligent systems, using appropriate techniques to manage large volumes of data, using appropriate techniques for labelled and unlabelled data, while understanding limitations caused by data bias (data).

Engineer solutions in which intelligent systems are used to solve real-world problems at scale, using knowledge and skills across the full breadth and depth of computational, machine learning, and mathematical principles (engineering).

Make immediate and effective contributions as part of multidisciplinary teams in industry, consultancy or education, by managing workloads, optimising resources and meeting deadlines, using experiences from team projects (team working).

Operate as responsible AI practitioners, by maintaining awareness of the safety, ethics and security of intelligent systems, how they can impact on society, and by continuing to expand and deepen their knowledge through critical engagement with the discipline (professionalism).

Teamwork is an important part of computer science. Therefore, you’ll spend time discussing maths problems and working on group projects, which can be great fun!

Will, Computer Science student

Fees and funding

Annual tuition fees for 2023/24

Study modeUK (home)International and EU
Full-time (1 year) £11,770£27,200

Students on a Student Visa (formerly Tier 4 Visa) are not currently permitted to study part-time at York.

Fees information

UK (home) or international fees? The level of fee that you will be asked to pay depends on whether you're classed as a UK (home) or international student. Check your fee status.

Find out more information about tuition fees and how to pay them.

Funding information

Discover your funding options to help with tuition fees and living costs.

We'll confirm more funding opportunities for students joining us in 2023/24 throughout the year.

If you've successfully completed an undergraduate degree at York you could be eligible for a 10% Masters fee discount.

Funding opportunities

Living costs

You can use our living costs guide to help plan your budget. It covers additional costs that are not included in your tuition fee such as expenses for accommodation and study materials.

Teaching and assessment

You’ll work with world‐leading academics who’ll challenge you to think independently and excel in all that you do. Our approach to teaching will provide you with the knowledge, opportunities, and support you need to grow and succeed in a global workplace.

Teaching format

Part of the course is taken up by taught modules. Each module comprises a mix of lectures, problem classes and practical classes, plus personal study time. You'll also undertake an individual research project under the supervision of a member of staff.

Throughout the course you will have a personal tutor, who will provide academic and pastoral advice. When you undertake your individual project, you will be allocated a supervisor within your area of interest. You should expect to be working on open assessments during vacation periods.

Facilities

The Department houses four software and two hardware laboratories.

Our Interaction Labs provide excellent facilities for research and teaching in human-computer interaction. The Interaction Labs consist of an Accessibility and Usability Lab and a Games Research Lab, both of which are stocked with the latest technologies.

Our Real Time Systems Lab is the main research and development facility for the Real Time Systems research group. Inside the laboratory is a range of high-performance computers, custom hardware like FPGAs, robots, and various industrial machinery.

The Computer Vision group has a darkroom laboratory which enables us to conduct experiments in controlled illumination conditions and a second laboratory which includes a commercial 3D scanner.

Our Robotics Laboratory is a purpose-built laboratory used for various robotics research projects and teaching. Within it, there is a dedicated student working area with workstations and electronics bench equipment, alongside the main 80m2 robotics arena. The arena features a 5.5m high ceiling allowing drone experiments to take place as well as ground-based robots. Special tracking systems are installed to allow positional data of the robots to be extracted. There is also a workshop area with CAD, soldering and 3D printing facilities.

Find out more about our facilities, including a video tour, showing our labs, teaching and research spaces.

Teaching location

Computer Science is based on Campus East. The majority of teaching on this course takes place on Campus East in the Computer Science building and Ron Cooke Hub.

Due to the intensive nature of the course, you will need to be in York throughout both semesters and over the summer while you undertake your individual project.

About our campus

Our beautiful green campus offers a student-friendly setting in which to live and study, within easy reach of the action in the city centre. It's easy to get around campus - everything is within walking or pedalling distance, or you can always use the fast and frequent bus service.

Assessment and feedback

We assess modules in a variety of ways, including practical exercises, reports and closed examinations. Your project assessment will be made up of a dissertation.

Assessments take place at various times during the year. Closed examinations are taken in the three-week assessment periods at the end of each semester.

Practical exercises, reports and other forms of open assessment typically occur towards the end of the teaching sessions of a module. Work for these assessments must be submitted by fixed deadlines normally well after the conclusion of the taught sessions.

Virtual tours

Take a virtual tour of one or our modern, dedicated facilities.

Our study and social pod is open 24/7 for group and individual study and events. It comes with a fully equipped kitchen.
Our dedicated hardware labs will introduce you to the basics of computer architecture, operating systems and program language construction, providing a basis for further study in later years.

Careers and skills

Skills for employability are embedded throughout the programme, with opportunities for you to return to these throughout the degree. Throughout the programmes, you'll study real cases from the industry, learn how to run projects and manage risks.

Career opportunities

  • Programming engineer
  • Software developer​
  • Higher education teaching and research
  • Information analyst and app developer
  • Systems architect
  • Business analyst
  • Artificial intelligence researcher

Transferable skills

  • Advanced computational skills
  • Project management and organisation
  • Project evaluation
  • Communication and time-management skills
  • Research skills

Entry requirements

Typical offer
Undergraduate degree 2:1 or equivalent in a Computer Science related degree, with a strong background in computer science, software engineering or information technology
Other international qualifications Equivalent qualifications from your country

English language

If English isn't your first language you may need to provide evidence of your English language ability. We accept the following qualifications:

Minimum requirement
IELTS (Academic and Indicator) 6.5, with 6.0 in each component
C1 Advanced and C2 Proficiency 176, with 169 in each component
Duolingo 120, with 105 in each component
LanguageCert SELT B2 with 33/50 in each component
LanguageCert International ESOL B2 Communicator: Pass with 33/50 in each component
PTE Academic/PTE Academic Online 61, with 55 in each component
TOEFL 87, with 21 in each component
Trinity ISE III Level 3 with Merit in each component

For more information see our postgraduate English language requirements.

If you've not met our English language requirements

You may be eligible for one of our pre-sessional English language courses. These courses will provide you with the level of English needed to meet the conditions of your offer.

The length of course you need to take depends on your current English language test scores and how much you need to improve to reach our English language requirements.

After you've accepted your offer to study at York, we'll confirm which pre-sessional course you should apply to via You@York.

Applying

You can apply and send all your documentation electronically through our online system. You don’t need to complete your application all at once: you can start it, save it and finish it later.

Apply for this course

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Department of Computer Science

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