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MEng (Hons) Computer Science with Artificial Intelligence

Study how human reasoning can be imitated or surpassed by computer systems.

Year of entry: 2020

UCAS code

G4G7

Institution code

Y50

Length

4 years full-time (plus optional placement year)

Typical offer

AAA/AAB (full entry requirements)

Start date

September 2020 (term dates)

UK/EU fees

£9,250 per year (2020/21)

International fees

£22,080 per year (2020/21)

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Study the development of computational systems that can perceive, learn, store information, reason about what is known, communicate using human language and interact with the physical environment.

On this integrated Masters, you will gain a thorough grounding in computer science then focus on themes such as natural language processing, machine learning, computer vision, intelligent agents and game AI.

Engage with the latest, cutting-edge research and benefit from our fantastic links with industry, potentially working on real-world projects specified by industry leaders.

Our courses are designed with our Industrial Advisory Board, so you’ll be well placed to adapt to the workplace.

This course is also available as a five-year course with a year spent in industry. Please see MEng in Computer Science with Artificial Intelligence with a Year in Industry.

Accreditation

This course is recognised by BCS, the Chartered Institute for IT, for the purposes of fully meeting the educational requirement for Chartered IT Professional (CITP), CITP Further Learning and Chartered Engineer (CEng).

This course is also recognised by Institution of Engineering and Technology (IET) for the purposes of fulfilment of the educational requirement for CEng registration.

Find out more about our accreditation.

Research excellence

Our research ranked 7th overall in the UK and 5th for impact [Times Higher Education ranking of the 2014 Research Excellence Framework]

Quality teaching

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

Course content

All students will study our core topics in computer science, which we have designed to be consistent with the Association for Computing Machinery (ACM) curriculum guidelines. These core topics provide the fundamental knowledge that all computer science graduates should possess, and the foundation required to specialise in the third and fourth years. The core topics are structured into eight streams:

  • Theory
  • Software
  • Systems and Devices
  • Data
  • Human-Computer Interaction (HCI)
  • Intelligent Systems
  • Engineering
  • Cyber security

At least 25% of the course content will be in your specialist area of Artificial Intelligence. To recognise this, your degree title will reflect your specialism.

Study abroad

There are opportunities for you to spend time abroad during your course:

Year 1

You will focus on establishing a solid foundation regardless of your previous experience of programming and computing.

Core modules

Academic integrity module

In addition to the above you will also need to complete our online Academic Integrity module.

Year 2

Year Two of the course will build upon the solid foundations you will have laid down in Year One. You’ll take modules from streams 1 to 5 to deepen your learning and start on two further streams studying intelligent systems and undertake a group engineering project. You should develop your interests which you will then begin to focus on in Year Three.

Core modules

  • Theory 3: Computational Complexity (10 credits)
  • Software 2: Functional Programming with Applications (10 credits)
  • Systems and Devices 2: System Software and Security (10 credits)
  • Systems and Devices 3: Advanced Computing Systems (20 credits)
  • Data 2: Data Analysis and Management (10 credits)
  • Human Computer Interaction 2: Interaction Design (10 credits)
  • Intelligent Systems 1: Search and Representation (10 credits)
  • Intelligent Systems 2: Machine Learning and Optimisation (20 credits)
  • Engineering 1: Introduction to Software and Systems Engineering (20 credits)

Year 3

When you return in Year Four, you will really get under the skin of the specialist areas which interest you.

Core modules

  • Project preparation
  • Individual project

You will also take modules covering the following stream:

  • Systems and Devices

Option modules

You’ll select options from topics related to Artificial Intelligence, such as:

  • Neural networks
  • Games AI
  • Machine learning
  • Probabilistic graphical models
  • Computer vision

Additional options from a range of topics, such as:

  • Real-time systems
  • Embedded systems
  • Specification, analysis and verification of systems
  • Computing by graph transformation

Year 4

In Year Four, you will work on a team engineering project which will be designed in collaboration with industry partners and take modules which access departmental research at an advanced level.

Core module

  • Team engineering project

Option modules

You’ll select options from topics related to Artificial Intelligence, such as:

  • Intelligent agents
  • Evolutionary computing
  • Constraint programming

Additional options from a range of topics, such as:

  • Critical systems
  • Model-driven engineering
  • Privacy and security
  • Quantum computing
  • Software testing

Please note, modules may change to reflect the latest academic thinking and expertise of our staff.

Learning by design

Every course at York has been designed to provide clear and ambitious learning outcomes. These learning outcomes give you an understanding of what you will be able to do at the end of the course. We develop each course by designing modules that grow your abilities towards the learning outcomes and help you to explain what you can offer to employers. Find out more about our approach to teaching and learning.

Students who complete this course will be able to:

  • Apply computational thinking to problems they encounter, using skills in problem analysis, representation and abstraction, and in algorithm selection, at different scales in complex situations, drawing on the foundations of computer science but with an awareness of current research issues and areas of commercial development.
  • Adapt to new technologies, languages, paradigms, terminologies and models as they become available, being confident to use cutting-edge techniques and tools in their practice, informed by self-directed study of current research and scholarship, and by awareness of open-source systems and tools.
  • Design and build computer-based systems to serve the needs of users and the commercial imperatives of an employer, with the most appropriate combination of software and hardware, by applying the theory and practice of programming and software engineering, while making effective use of the variety of physical implementations on which that software may be running.
  • Engineer AI (Artificial Intelligence) systems that operate independently or in conjunction with other software systems by rigorous understanding of the problem domain by using skills from the whole breadth of Computer Science across all parts of the development lifecycle, with deeper skills in AI.
  • Make immediate and effective contributions as part of multidisciplinary teams in industry, consultancy or education, by organising themselves to manage workloads, optimise resources and meet deadlines, using experiences from team projects.
  • Communicate and negotiate with technical and non-technical stakeholders about complex computational problems and their solutions in a clear and organised manner, with compelling and convincing arguments.
  • Operate as responsible Computer Science professionals, by maintaining awareness of key legal and ethical issues, appreciating how computers and technology can impact on society and the importance of risk management, and by continuing to expand and deepen their knowledge through critical engagement with the discipline.
  • Apply theoretical and practical knowledge of chosen areas of cutting-edge AI (Artificial Intelligence) and available commercial technology to new or unfamiliar problems they encounter in employment or further study, and to communicate the results in a significant technical report or other appropriate medium.

Fees and funding

Annual tuition fees

UK/EU International
£9,250 £22,080

Additional costs

There are unlikely to be any mandatory additional costs associated with the course, although you may want to set aside £200 for optional photocopying and personal stationery over the duration of the course.

UK/EU or international fees? The level of fee that you will be asked to pay depends on whether you're classed as a UK, EU or international student.

Fees for subsequent years

  • UK/EU: further increases within the government fee cap will apply in subsequent academic years. We will notify you of any increase as soon as we can.
  • International: fees for international students are subject to annual increases. Increases are currently capped at 2% per annum.

More information

For more information about tuition fees, any reduced fees for study abroad and work placement years, scholarships, tuition fee loans, maintenance loans and living costs see undergraduate fees and funding.

Funding

We'll confirm more funding opportunities for students joining us in 2020/21 throughout the year.

We have a number scholarship opportunities available for students in 2018/19, including three IBM scholarships.

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 Excellence Framework Gold Award

“Students from all backgrounds achieve consistently outstanding outcomes”

The TEF Panel, Office for Students, June 2018

Our Gold Teaching Excellence Framework award demonstrates our commitment to the delivery of consistently outstanding teaching and learning for our students.

Teaching and assessment

You’ll study and learn with academics who are active researchers, experts in their field and have a passion for their subjects. Our approach to teaching will provide you with the knowledge, opportunities, and support you need to grow and succeed in a global workplace. Find out more about our approach to teaching and learning.

Teaching format

A typical week will involve about 15-20 hours of scheduled teaching time. Our courses are based on a series of one-hour lectures with associated laboratory sessions, programming classes and tutorials.

Throughout the course, you will have a personal supervisor responsible for guiding your studies. In addition to any timetabled sessions, you will meet with your supervisor regularly, and you can also go to them at any time should you have any issues, academic or personal. There are problem classes to help you put learning from lectures into practice and one-to-one weekly project supervisions in your final year.

You will also undertake learning outside of the scheduled timetable. This can be through working in the labs, which are accessible 24 hours a day, seven days a week, or through reading recommended materials or working through problems. Consequently, you'll need to be self-motivated, self-disciplined and willing to learn outside regular classes.

As you progress through the course you will develop your skills to become a more independent learner. You'll also spend time working on your individual research project later on in the course, in addition to timetabled activity; you will be allocated a project supervisor, with whom you will have regular meetings in addition to timetabled sessions. You can go to your supervisor for support and advice regarding your project.

Overall workload

As a guide, students on this course typically spend their time as follows:

Year 1Year 2Year 3Year 4
Lectures and seminars420 hours348 hours264 hours180 hours

The figures above are based on data from 2016/17.

The rest of your time on the course will be spent on independent study. This may include preparation for classes, follow-up work, wider reading, practice completion of assessment tasks, or revision.

Everyone learns at a different rate, so the number of hours will vary from person to person. In UK higher education the expectation is that full-time students will spend 1,200 hours a year learning.

Facilities

Built to the highest specifications, the Department is packed with cutting-edge facilities housed in a modern, self-contained building.

The Department houses four software and two hardware laboratories which you will be able to use depending on the topic of your third year project. These facilities are professional grade and used by our research teams so, depending on your interests, you'll get first hand exposure to these environments.

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 have 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

The Department of Computer Science is based on Campus East. The majority of your teaching will take place in the department, with additional teaching taking place at other locations on Campus East.

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 use a variety of assessment techniques throughout your course. This allows you to practice different techniques, from report writing, presentations and live demos to timed programming assessments and closed exams. It also means that you are not disadvantaged by being assessed in any one way.

We provide exam review sessions, where you can come and see your marked assessment and ask an academic member of staff any questions about the way it has been marked. We also provide you with electronic feedback, which is given alongside the marks you receive. We also have a Board of Examiners, to which any student can apply if they wish to take queries about their assessments further.

We also ask our students for feedback on the course and assessments at the end of each year. This helps to improve and modify what we do to help meet the needs of our students.

 

Percentage of the course typically assessed by coursework and exams

Year 1Year 2Year 3Year 4
Written exams56%64%80%8%
Coursework11%31%12%92%
Practical exams33%5%8%0%

The figures above are based on data from 2016/17.

Careers and skills

The move towards a digital economy creates demand for computer scientists and software engineers across a broad section of employers, so the skills you develop here will make you attractive to many organisations. Most of our graduates go into the field of IT/Computing, followed by Financial Services, some undertake further study (eg PhD) and others go straight into industry (for example working for IBM, BAE Systems etc).

Many of our graduates are employed by software and electronics industries, but the continuing expansion of the use of computers in commercial and financial operations means that you will be able to find employment in other industries - and here your sharpened numeracy and analytical skills will have prepared you well.

Read some profiles of our past students and find out how their degree from York helps them to do jobs in organisations as diverse as Mars Inc and Cancer Research UK. Other companies that York graduates have gone on to work for include BAE Systems, Morgan Stanley, G Research, Thales, the Civil Service, M&G Investments, Ubisoft, Rapita Systems, Sky, BT, Raspberry Pi, IBM, JP Morgan, Hut Group and Automaton Games.

Computer Science graduates can expect to earn nearly £40,000 after five years in employment (Longitudinal Education Outcomes Dataset).

Career opportunities

  • Computer Programmer
  • Software Engineer
  • Software Developer
  • Business Analyst
  • Research Scientist
  • Network Manager
  • IT Systems Manager

Transferable skills

At York, you will gain a broad understanding of all of the essential scientific principles, engineering techniques and practices in Computer Science. This allows you to be flexible and adapt quickly in any field that you wish to go into. More specifically, we can identify four main skill areas as follows:

  • Analytical skills. The ability to approach problems analytically, and to design structured solutions. Laboratory modules will help you to develop skills of data analysis, design and implementation. You will also be introduced to a wide range of modern software development tools and techniques.
  • Research skills. Throughout the course you will be given opportunities to learn research skills. These culminate in a major final year project where you will research a problem, identify the key issues, produce a critical assessment of the relevant literature, and generate a new solution.
  • Management skills. You will have the opportunity to learn about the techniques, concepts and theories used in project management, and gain experience of putting them into effect.
  • Communication skills. Communication skills are invaluable. You will have the opportunity to develop these skills through, for example, oral and written presentations, in both formal and informal settings. At the end of the course, you will be confident and competent in communicating your knowledge and skills to a wide range of audiences.

Entry requirements

Qualification Typical offer
A levels

AAA/AAB including Mathematics

Access to Higher Education Diploma We accept the Access to Higher Education Diploma. The syllabus must contain a significant portion of Mathematics that is considered equivalent to A level standard. Applications will be considered on an individual basis - please contact the Department before you apply.
BTEC National Extended Diploma DDD and grade A in A level Mathematics (or equivalent qualification). We consider applicants with a combination of other BTEC Level 3 qualifications, and this must include grade A in A level Mathematics (or equivalent qualification). Please contact us to discuss your combination of qualifications
Cambridge Pre-U D3/D3/D3 - D3/D3/M2 including Mathematics
European Baccalaureate 85% - 80% overall, including at least 80% in Mathematics
International Baccalaureate 36 - 35 points overall, including grade 6 in Higher Level Mathematics
Other qualifications We welcome applications offering a mix of OU, A level and other appropriate qualifications. Applications will be considered on an individual basis: please contact the Department before you apply.

We require a qualification in a physical science; for example, a GCSE at grade 4 (C) or above in Physics or Double Science, or Science and Additional Science.

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:

Qualification Minimum requirement
IELTS 6.5, with a minimum of 6.0 in each component
PTE Academic 61, with a minimum of 55 in each component
GCSE/IGCSE/O level English Language (as a first or second language) Grade C
C1 Advanced and C2 Proficiency 176, with a minimum of 169 each component
TOEFL 87 overall, with a minimum of 21 in Listening, 21 in Reading, 21 in Speaking, 21 in Writing
Trinity ISE III Merit in all components

For more information see our undergraduate 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 IELTS 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

To apply to York, you will need to complete an online application via UCAS (the Universities and Colleges Admissions Service).

Next steps

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Department of Computer Science

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