Three years full-time.
Four and a half to nine years part-time.
2023-24 entry; 112 UCAS tariff points (or above), BBC (A-Level), DMM (BTEC)
This course is provided as a pathway on our BSc (Hons) Computing degree. All students begin their studies on the BSc (Hons) Computing degree before choosing the artificial intelligence pathway towards the end of their first year of study. Students who complete this pathway will receive the specialist BSc (Hons) Computing (Artificial Intelligence) award at graduation.
It is estimated that we currently produce over 2.5 quintillion bytes of data every single day. This data includes over 94 million photos and videos shared on Instagram, over 306 billion emails and over 5 million Tweets. In the last two years alone, an astonishing 90% of the world’s data has been created.
The artificial intelligence pathway on our BSc (Hons) Computing degree has been designed to provide you with everything you need to be able to find meaning in this data as a successful data scientist and artificial intelligence expert.
- Access to our state-of-the-art DigiTech Centre for specialist modules.
- Access to resources from some of the largest tech companies including Amazon Web Services, Juniper, Oracle and our new Google Student Club
- An opportunity to start your own artificial intelligence business with the University of Suffolk’s Innovation Centre (IWIC) and gain guidance from business leaders and academics.
In the first year of the course, you will gain a solid foundation in data science, artificial intelligence, programming, networks and computer systems. In the second year, you will have the opportunity to create a substantial software product that incorporates software design, implementation and testing. You will also undertake the courses core research skills module in preparation for your final year project and dissertation. During the final year of your course, you will complete your final project and dissertation. For this, you will be assigned a supervisor who is familiar with your chosen topic. You will also study advanced modules in data science, artificial intelligence, cyber security and distributed systems preparing you for a career as a data scientist.
Throughout the course, you are also encouraged to attend an extensive range of seminars and events provided by guest lecturers with backgrounds in technology, business and academia. These same experts often provide real-world briefs for module assessments allowing you to undertake a project specified by industry to meet an organisation’s real needs.
How will you be taught?
You will be taught by experienced lecturers who use their years of industry and research knowledge to demonstrate best practices, industry standards and innovative technologies. You will experience a variety of teaching methods including lectures and seminar sessions, totalling at least 12 hours of contact time per week. You will also have access to our virtual learning environment, Brightspace allowing you 24/7 access to lecture material and activities, both on and off campus.
Students also have access to our computing Slack channel allowing them to collaborate and chat with each other. New computing students joining the university will receive access to our ‘New Student’ Slack channel in the weeks before the course commences. This allows new students to get to know each other and make friends before they arrive on campus.
How will you be assessed?
Throughout the course, the emphasis is placed on students completing hands-on projects that they can later present in their professional portfolio to employers. A variety of assessment methods are used, including individual and group-based practical projects, quizzes, technical reports and presentations. There are opportunities for feedback on your work throughout and you will receive the support you need through your lecturers and our academic support and library services teams.
How do you ask a question?
You can click here at any time to contact a lecturer or student studying on our computing degree. Do feel free to ask any questions about the computing course, our pathways, the university, student life and services or anything else.
How do you apply?
To join our artificial intelligence pathway, please apply for our BSc (Hons) Computing degree (UCAS code I103). All our students begin on this degree and then have the option of selecting a specialist pathway in cyber security, web and mobile development or artificial intelligence towards the end of their first year.
Full downloadable information regarding all University of Suffolk courses, including Key Facts, Course Aims, Course Structure and Assessment, is available in the Definitive Course Record.
All students on the artificial intelligence pathway will take the following six required modules in their first year:
This module covers the principles of computer systems, hardware components, the essence of operating systems, and relevant computing-related mathematics. This module will provide the foundational underpinning to enable students to progress deeper into the disciplines of computing and networking, and a grasp of the history of computing, recent developments and its possible future.
Introduction to Networking
This module introduces the concepts of communications and networking. It explores the Open Systems Interconnectivity (OSI) 7-layer reference model and TCP/IP Routing Suite (the 5-layer Internet reference model). TCP/IP is the model which is most commonly deployed in the majority of modern-day networks.
Introduction to Web Design
Introduction to Programming
This module introduces students to the concepts and practice of computer programming. It is aimed at providing students with an understanding of the fundamentals of computer programming by having them work through a range of tasks focused upon layout, structure and functionality. The core language taught is Python but C++ is also introduced.
This module will introduce the concepts of operating systems, including their structure, memory and storage management, protection and security. Designed with software developers in mind, it will look closely at real-world operating systems such as Windows and UNIX.
- Introduction to AI and Data Science
This module provides an introduction to the artificial intelligence and data science fields, covering the history of the discipline, exploring a variety of “classical AI” topics and the application of Python to solve data problems.
All students on the artificial intelligence pathway will take the following six required modules in their second year:
Software Design, Development and Engineering
This module focuses on all phases of the modern software engineering lifecycle and advanced software engineering topics, including critical software, secure software, formal methods and project management from the practitioner’s perspective. This will be put into practice through the requirements gathering, design, implementation and testing of an extensive project that meets the needs of a particular enterprise.
This module provides essential knowledge and appreciation of the role of relational database systems, including basic principles and practice of design, implementation and development for both system designers and software engineers. It will include practical exercises in Structured Query Language.
Computing Research Skills, Professional Practice and Ethics
Research skills are an essential set of capabilities in the toolkit of a professional software engineer. In this module, students will develop knowledge and understanding of the purpose, processes, methods (surveys, experiments, interviews, case studies, etc.), analysis (qualitative and quantitative), and outputs of research and will be able to apply them. This module also delves into the professional, legal and ethical standards and guidelines that inform and guide best practice in business and computing.
Data Structures, Algorithms and Advanced Programming
This module focuses on data structures (e.g. linked lists, trees, heaps, hash tables, etc), algorithms (sorting, searching, dynamic programming, greedy, graph, geometric, cryptographic, string matching and compression algorithms, etc), and advanced programming techniques and other language paradigms.
Data Mining and Statistics
Data science includes many techniques for classification, analysis and prediction. This module focuses on those techniques relating to data mining and statistically driven approaches. These techniques also have the advantage of being “explainable AI”, more so than deep learning approaches, and some are long established techniques of “business intelligence”.
Industry, commerce and research are being transformed by the potential to capture, store, manipulate, analyse and visualise data and information on a massive scale. The advent of Big Data with its variety, velocity and volume disrupted the way we store and manage data. During this module you will learn NoSQL approaches to data modelling, database design and manipulation.
All students on the artificial intelligence pathway will take the following three module in their third year:
Project and Dissertation
The module provides the opportunity for students to apply and develop some of the knowledge and skills acquired in their degree by engaging in a significant project in a specialist area of computing, typically software or networks. It will enable and require students to utilise practical, intellectual and decision-making skills in novel situations and develop their autonomy and self-direction.
Neural Networks and Deep Learning
A sufficiency of inexpensive computing power, sufficiently large datasets and a number of key theoretical advances created deep learning techniques which have facilitated a wave of accuracy increases across many computational tasks (computer vision, natural language processing, speech recognition, autonomous driving, etc.), making many applications practical. Deep learning is central to modern artificial intelligence. This module explains the underlying mathematics and techniques and how to use them to achieve similar feats of computational accuracy.
AI and Data Science Applications
This module provides an opportunity to explore in greater depth several areas of artificial intelligence and data science. This will include an understanding of the domain theory, typical problems faced in the domain and how these might be solved.
In addition to the above module, students are required to choose two of the below optional modules:
This module provides a systematic understanding of distributed operating systems, software services and applications in terms of their architectures, functionality and behaviour. It includes case studies on the “Internet of Things” and cloud computing as well as topics on parallel programming.
Mobile Application Development
The module is intended to provide students with an understanding of development for mobile devices with a focus on the constraints of mobile hardware, including interface and networking. Students will learn to integrate input from hardware sensors and work with networked data and services.
Cyber Security: Attack and Defence
On one hand, this provides insights into the mindset of cyber attackers, a secure understanding of the ethics and legal issues in this area, and knowledge and skills in attack technologies and techniques. On the other hand, this module provides a detailed knowledge and understanding of the techniques and tools available to a security professional, and the practical skills in selecting, evaluating, designing, implementing and deploying defences to protect vulnerable software, networks and systems.
Our pathway in artificial intelligence will provide you with the knowledge and skills required to become a career-ready graduate. The University of Suffolk’s Innovation Centre (IWIC) provides students will the opportunity to start a business with business and academic guidance, facilities and support. Students who graduate on this pathway could also pursue a career in one of the following roles:
- Data Scientist
- Artificial Intelligence Expert
- Data Analyst
- Data Engineer
- Machine Learning Engineer
- Data Architect
- Business Analyst
Fees and finance
- UK full-time tuition fee: £9,250 p.a
- UK part-time tuition fee: £1,454 per 20 credits (please contact the Student Centre for further information)
- International full-time tuition fee: £14,598 p.a
At University of Suffolk, your tuition fees provide access to all the usual teaching and learning facilities that you would expect. However, there may be additional costs associated with you course that you will need to budget for.
* 2023-24 tuition fees are subject to change in line with inflation, or a government change in the fee cap.
Please call our Clearing Hotline, 01473 338348, to discuss your qualifications and suitability for 2022 entry.
Applicants are also required to have GCSE Maths grade 4/C or above, or equivalent Level 2 qualification. Applicants who do not hold these qualifications may be considered on an individual basis based upon their overall application and the course applied for.
If you have previously studied at higher education level before you may be able to transfer credits to a related course at the University of Suffolk and reduce the period of study time necessary to achieve your degree.
Facilities and Resources
The majority of teaching on this degree will take place on our main Ipswich Waterfront campus. This location was opened in 2016 and received a £5.5 million-pound investment in both the building and the facilities on offer. The top floor of the Atrium houses four high-end computer laboratories complete with industry-standard software and tools.
Specialist modules in data science, artificial intelligence and cyber security may also take place in our state-of-the-art DigiTech Centre at Adastral Park, which was unveiled by Her Royal Highness the Princess Royal in November 2019 and launched in the summer of 2021. A collaboration between the University of Suffolk and BT, with funding from the New Anglia Local Enterprise Partnership (LEP), the centre has been established to provide training in cutting-edge digital skills for people looking to pursue careers in the nationally-important information and communications technology (ICT) sector, as well as fuelling high tech businesses who increasingly require access to a talented technology workforce.