BSc Computer Science (Artificial Intelligence)

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BSc Computer Science (Artificial Intelligence)

Choose a career-driven degree. Apply for Computer Science (Artificial Intelligence) at Hull today.

Key information

Study mode

Full-time

Course length

3 years

Typical offer

112 points

A Level grades: BBC

UCAS code

G700

Choose an option

Start date

Course overview

Artificial intelligence is rapidly transforming the way we live and work.

From self-driving cars to medical diagnosis, AI and machine learning systems are helping people make better decisions, improve safety and even reduce our carbon footprint. Techniques like deep learning and the integration of big data are increasingly giving computers the ability to operate and make sensible decisions in our messy, unstructured world.

Our AI-focussed programme will give you a solid grounding in Artificial Intelligence and Computer Science and equip you with the knowledge and skills you’ll need to be part of the AI future.

Learn advanced Python programming skills and develop your own software using industry standard techniques and tools. Learn about essential areas such as databases and networks, operating systems and the cloud. Gain specialist knowledge and experience in the development of intelligent systems, including machine learning, algorithms and complexity and visual computing.

And we don’t just focus on the technology - you’ll also study the increasing impact of AI on everyone in society.

Our degree is designed with your future career in mind. In your first year, you’ll take a module on professional development, while in your final year there is the chance to develop your own project, which you can show to employers when you apply for jobs.

There is also the option to spend a year in industry on a guaranteed paid placement. Taken between the second and third years, this forms a recognised part of your degree. (Foundation year students would need to transfer to a BSc or MEng programme to take this option).

When you join us, you’ll get access to the latest industry-standard facilities, including high-performance workstations, gigabit networking, swarm and humanoid robots, VR headsets, a 3D immersive cube, motion capture, AR and MR. We are ranked sixth in the UK for learning resources in Computer Science. And it’s all here on our single-site campus for you to use.

Our courses are shaped by our world-leading research in areas such as artificial intelligence and machine learning, intelligent and interactive systems, robotics, simulation, visualisation, and mobile and distributed computing.

When you are not studying there are plenty of extra-curricular activities for you to get involved in, such as student societies, hackathons and networking events with employers.

Cutting edge facilities to complement cutting edge learning

Computer Science

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Six reasons to study Computer Science (Artificial Intelligence) at Hull

  1. 94.4% graduate employability rating†
  2. Top 5 UK university for research impact
  3. 6th in the UK for learning resources in Computer Science
  4. Guaranteed industrial placement (optional)
  5. Superlab, high-performance workstations, gigabit networking
  6. Robotics lab with humanoid Baxter, Nao Robots and DJI drones
This course is British Computer Society (BCS) accredited

What you'll study

The course consists of 120 credits per year. Most modules are 20 credits, meaning you’ll study six modules each year. Some longer modules, such as a dissertation, are worth more (e.g. 40 credits). In these cases, you’ll study fewer modules - but the number of credits will always add up to 120.

First year modules

  • Core

    Computational Thinking

    This module will enable you to develop your knowledge and understanding of the key mathematical underpinnings of computer science, to aid you in problem solving and programming. The development of your competence in logic, mathematics and statistics will also provide evidence of your numeracy and more advanced skills and is valued by employers.

    Algorithms and Data Structures

    Start to think like a computer (bleep bloop)! This module explores logic, data storage and algorithms with the use of practical demonstrations and activities. Operating in parallel with programming-focussed modules, we will develop a toolkit of key concepts from a theoretical (non-code) perspective, facilitating a better understanding of these fundamentals. Topics to expect include pseudocode, state machines, essential keywords, common data structures, sort algorithms and search algorithms. You will learn methods to analyse and compare algorithms and their constituent parts in order that you may better design, evaluate and develop effective, efficient and performant software solutions.

    Programming Portfolio

    This module provides the required practical knowledge for Computer Science students to design, implement and test algorithms. The module uses lectures to deliver concepts, a practice lab to apply the programming concepts learnt by developing programs to solve problems. You will take part in hands-on practical assessments, which will enable you to acquire extensive programming skills in an industry standard programming language. We will support you whether you are new to programming or have existing skills.

    Architectures, Operating Systems and the Cloud

    Explore the fundamental properties of computers that allow them to execute programmes. You will learn about how Computers are made to work in hardware and simulation (Virtual Machines). A collection of Virtual Machines is a cloud, and this module allows you to get experience with the development of your own cloud using appropriate platforms.

    Professional Development (Computer Science)

    Employers want much more than discipline specific skills. This module sets you up to grow your professional skills and awareness, when working both individually and as part of a team. You will also develop your appreciation of the challenges within the sector, and how technology can help to solve worldwide issues. You will begin a personal portfolio that you will add to over your degree and you will work as part of a team to produce a design prototype, demonstrating your personal professional development. Through researching your discipline, you will understand the range of career roles available and what you need to do to progress in them.

Second year modules

  • Compulsory

    Design, Develop, Deploy

    Our flagship software development module. You'll use contemporary software development tool chains to experience authentic software creation and deployment, applying techniques such as agile project management, test-driven development and continuous integration and deployment.

    Databases and Networks

    You'll be introduced to the core components of any online information system that drives the information we use today. Learn how modern applications fetch data from servers and how that information can be stored and retrieved efficiently. You will solve a real-world problem by developing a networked database.

    Artificial Intelligence

    Learn about classical AI techniques – how to represent knowledge and how to use it to reason about the world. You’ll consider some of the important techniques such as logic programming, rule based reasoning, knowledge searching and pathfinding, and how to implement them in code and apply them to real-world problems.

    Applied Artificial Intelligence

    Artificial Intelligence has become the cornerstone for an increase of efficiency and productivity.  In this module you’ll be introduced to the fundamental tools of AI using a hands-on, applied approach. As a result, you will be able to begin analysing, validating and interpreting automated decision making.

  • Optional (choose 1)

    Advanced Programming

    In this module you will explore advanced techniques in programming as well as building an understanding of how high level objected-oriented languages are executed on a modern CPU.  C++ will be used extensively, but we with reflect back on C#, as well as throwing in some assembly language.

    User Interfaces and Experience

    Any software or hardware used by humans needs to put human understanding at its core. Digital products succeed or fail by how well the designer understands the ability of a human to use the product, or the experience that using the product provides. You'll take a scientific and engineering approach to understanding, developing and evaluating effective interfaces and experiences for users.

    Mixed Reality Development

    Mixed Reality is a blend of physical and virtual environments, unlocking natural and intuitive 3D human, computer, and environment interactions. Learn concepts and techniques in the field of mixed reality and user-centred testing and implement mixed reality applications using technologies applicable to the problem domain. You will use a mixed reality application to conduct a user test, analyse and report on results.

Final year modules

  • Optional (choose 1)

    Honours Stage Project (Computer Science & AI)

    Your Honours Stage Project is your chance to spend a full third of your study time working on a topic of interest to you and producing something major as a result.  You can design your own project, work with a member of staff to develop an idea, or choose one from a catalogue.  Develop an AI program, do some research in virtual reality, or build a new robot butler – the choice is yours.  With regular support from a supervisor, you’ll learn to create, undertake, evaluate and report on a significant individual project which you’ll be proud to show off to an employer.

    Communicating and Teaching Computing

    This module enables you to undertake a placement in a school, college or other educational establishment where you can develop your practical teaching and communication skills, as well as extending your knowledge of the education process. These skills are valued by employers, whether you are interested in potentially going on to train or teach others or not. You will also have the opportunity to develop an educational project to demonstrate your skills in practice.

  • Compulsory

    Data Analysis and Visualisation

    Data analytics has rapidly become a part of all of our lives, and is an increasingly sought-after skill on the job market. In this module you'll learn the theoretical and practical skills to analyse any dataset independently, starting from exploratory analysis of a new dataset for hypothesis finding, over choosing and comparing different algorithms, and presenting and explaining your results quantitatively and visually. You will learn to train models of different complexity that can make predictions or uncover hidden patterns in data, making responsible and fair decisions that can help improve our lives.

    Machine Learning

    Machine learning comprises the theory and practice underlying recent advances in artificial intelligence and is a core requirement for anyone seeking to work in the AI or data analysis field. This module will introduce core algorithms in machine learning, including state-of-the-art deep learning models, and consider practical issues around complexity, optimisation and performance. You will learn to systematically compare algorithms and establish the mathematical foundations to implement your own. 

    Computer Vision

    Computer vision is fundamental to intelligent systems ranging from advanced microscopes to access control systems and from autonomous robots to self-driving cars. You'll will develop expertise that are currently being used in real-world systems. This includes design and analysis of algorithms for image processing and computer vision as well as evaluation of various cutting-edge solutions in the context of emerging applications.

    Computational Science

    Study the key concepts and techniques to: enable modelling a system, understand its limitations and develop appropriate AI architectures to solve computational problems.

All modules are subject to availability and this list may change at any time.

How you'll study

Throughout your degree, you’re expected to study for 1,200 hours per year. That’s based on 200 hours per 20 credit module. And it includes scheduled hours, time spent on placement and independent study. How this time’s divided among each of these varies each year and depends on the course and modules you study.

Overall workload

If you’re enrolled on a full-time programme of study, you’ll be expected to complete about 40 hours of academic work each week.

How you’ll learn

Indicative assessment proportions

53%
7%
40%
  • Examination

    Written assessment typically includes exams and multiple choice tests.

  • Practical

    Practical is an assessment of your skills and competencies. This could include presentations, school experience, work experience or laboratory work.

  • Coursework

    Coursework typically includes essays, written assignments, dissertations, research projects or producing a portfolio of your work.

Overall workload

If you’re enrolled on a full-time programme of study, you’ll be expected to complete about 40 hours of academic work each week.

How you’ll learn

Indicative assessment proportions

52%
48%
  • Examination

    Written assessment typically includes exams and multiple choice tests.

  • Coursework

    Coursework typically includes essays, written assignments, dissertations, research projects or producing a portfolio of your work.

Overall workload

If you’re enrolled on a full-time programme of study, you’ll be expected to complete about 40 hours of academic work each week.

How you’ll learn

Indicative assessment proportions

35%
65%
  • Examination

    Written assessment typically includes exams and multiple choice tests.

  • Coursework

    Coursework typically includes essays, written assignments, dissertations, research projects or producing a portfolio of your work.

Sam Hutchinson, MSc Computer Science
Sam Hutchinson Computer Science

My placement year at BT

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Guaranteed, paid year in industry

Spend a year in industry getting real world experience with the added benefit of help from our award-winning careers service.

Explore our Placement Years
Students in the Computer Science Robotics Lab

Facilities

Get access to the latest industry-standard facilities, from high performance cloud computing systems and 3D projection to VR and humanoid robots.

Computer Science Facilities

Entry requirements

Typical offer

  • A level grades BBC

  • BTEC grades DMM

  • Points required 112

Work out your estimated points

Don't meet our requirements?

We offer a Foundation Year to boost your skills and knowledge – it’s a great way to make your way into higher education.

Switch to the foundation year

Points can be from any qualifications on the UCAS tariff, but must include at least 80 points from

  • A levels
  • BTEC Subsidiary Diploma, Diploma or Extended Diploma
  • OCR Cambridge Technical Introductory Diploma, Diploma or Extended Diploma
  • CACHE Diploma or Extended Diploma
  • Irish Leaving Certificate
  • Scottish Highers
  • Welsh Baccalaureate Advanced Diploma
  • or a combination of appropriate Level 3 qualifications

Applicants should also have

  • GCSE Maths at Grade 4 or C or above

Alternative qualifications

  • IB Diploma: 28 points
  • Pass Access to HE Diploma overall with a minimum of 112 UCAS tariff points

Worried you don’t quite meet our entry requirements?

We consider experience and qualifications from the UK and worldwide which may not exactly match the combinations above.

But it’s not just about the grades – we’ll look at your whole application. We want to know what makes you tick, and about your previous experience, so make sure that you complete your personal statement.

If you have any questions, our admissions team will be happy to help.

Don't meet our requirements?

We offer a Foundation Year to boost your skills and knowledge – it’s a great way to make your way into higher education.

Switch to the foundation year

If you require a student visa to study or if your first language is not English you will be required to provide acceptable evidence of your English language proficiency level.

This course requires academic IELTS 6.0 overall, with no less than 5.5 in each skill. See other English language proficiency qualifications accepted by this University.

If your English currently does not reach the University's required standard for this programme, you may be interested in one of our English language courses.

Visit your country page to find out more about our entry requirements.

Our lecturers

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Dr David Parker

Lecturer

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Fees and funding

UK

£9,250 per year*

EU/International

£18,300 per year

International applicants may need to pay a tuition fee deposit before the start of the course. Visit our tuition fee deposit page for more information.

*The amount you pay may increase each year, in line with inflation - but capped to the Retail Price Index (RPI).

UK students can take out a tuition fee loan to cover the cost of their course and a maintenance loan of up to £9,978 to cover living costs.

Substantial discounts are available for International students.  

More information on fees can be found in the Money section of our website.

Your tuition fees will cover most costs associated with your programme (including registration, tuition, supervision, assessment and examination).

There are some extra costs that you might have to pay, or choose to pay, depending on your programme of study and the decisions you make. The list below has some examples, and any extra costs will vary.

  • Books (you’ll have access to books from your module reading lists in the library, but you may want to buy your own copies)
  • Optional field trips
  • Study abroad (including travel costs, accommodation, visas, immunisation)
  • Placement costs (including travel costs and accommodation)
  • Student visas (international students)
  • Laptop (you’ll have access to laptops and PC’s on campus, but you may want to buy your own)
  • Printing and photocopying
  • Professional-body membership
  • Graduation (gown hire and photography)

Remember, you’ll still need to take into account your living costs. This could include accommodation, travel and food – to name just a few. 

An affordable city for students

From bills, to meals, to pints – you’ll find that your money goes a lot further in Hull.

Your future prospects

  •  Artificial Intelligence developer
  • Software engineer
  • Games or app developer
  • Data analyst
  • Software engineer
  • Analyst programmer
  • Cyber security analyst

AI and machine learning are embedded into modern living. As a result, Computer Science and AI graduates are highly employable and can go on to exciting careers in a diverse range of fields, performing a wide range of job roles.

It’s hard to imagine a sector of the modern economy where AI is not used. Sectors where graduates find employment include banking and finance, gaming, telecommunications, retail, information technology, advertising and marketing.

Open Day at University of Hull

Ready to apply?

You can apply for this course through UCAS. As well as providing your academic qualifications, you’ll be able to showcase your skills, qualities and passion for the subject.

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*National Student Survey (NSS) 2021, HEIs only.

† Percentage of students in work or further study within 15 months of graduating: UK domicile full-time first degree leavers, Graduate Outcomes survey for the academic year 2018/19, published by HESA July 2021.