STUDY

Undergraduate

BSc (Hons) Computing (Artificial Intelligence)

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Institution code: S82
UCAS code: I103
Start date: September 2024
Duration: Three years full-time, four and a half to nine years part-time
Location: Ipswich
Typical Offer: 112 UCAS tariff points (or above) BBC (A-Level) DMM (BTEC), Merit (T Level)
Institution code: S82
UCAS code: I103
Start date: September 2024
Duration: Three years full-time, four and a half to nine years part-time
Location: Ipswich
Typical Offer: 112 UCAS tariff points (or above) BBC (A-Level) DMM (BTEC), Merit (T Level)
Course information table
Institution code: S82
UCAS code: I103
Start date: September 2025
Duration: Three years full-time, four and a half to nine years part-time
Location: Ipswich
Typical Offer: 112 UCAS tariff points (or above) BBC (A-Level) DMM (BTEC), Merit (T Level)
Course information table
Institution code: S82
UCAS code: I103
Start date: September 2025
Course information table
Duration: Three years full-time, four and a half to nine years part-time
Location: Ipswich
Typical Offer: 112 UCAS tariff points (or above) BBC (A-Level) DMM (BTEC), Merit (T Level)

Overview

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.

Introduction

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. 

 

Course highlights

  • 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 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 practice, 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.

 

The University of Suffolk is world-class and committed to our region. We are proudly modern and innovative and we believe in transformative education. We are on the rise with a focus on student satisfaction, graduate prospects, spending on academic services and student facilities.

10th

in the UK for feedback satisfaction in Computer Science and Information Systems

(The Guardian University Guide 2023)

2nd

in the East of England for graduate prospects

(The Complete University Guide 2024)

11th

in the UK for social inclusion

(The Good University Guide 2023)

Course Modules

Our undergraduate programmes are delivered as 'block and blend', more information can be found on Why Suffolk? You can also watch our Block and Blend video.   

Downloadable information regarding all University of Suffolk courses, including Key Facts, Course Aims, Course Structure and Assessment, is available in the Definitive Course Record 

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 different computing specialisms, and a grasp of the history of computing, recent developments and its possible future. 

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.

The module introduces the concepts of web design, with a focus on designing responsive websites that are targeted at mobile platforms. Students are introduced to HTML, CSS and JavaScript to provide them with an understanding of what goes into the front-end of modern websites. Using a series of case studies, students will analyse the design and layout of a range of existing sites using a number of common analysis techniques.

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.

This module provides an understanding of why cyber security matters to businesses, to society and to individuals, coupled with knowledge of basic concepts, attack techniques, attacker types, and the core elements of cyber assurance.

This module provides an introduction to the artificial intelligence and data science fields, covering the history of the discipline, and exploring a variety of “classical AI” topics.

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. 

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.

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 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.

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. 

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.

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.

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.

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.

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.

Course Modules

Our undergraduate programmes are delivered as 'block and blend', more information can be found on Why Suffolk? You can also watch our Block and Blend video.   

Downloadable information regarding all University of Suffolk courses, including Key Facts, Course Aims, Course Structure and Assessment, is available in the Definitive Course Record 

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 different computing specialisms, and a grasp of the history of computing, recent developments and its possible future. 

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.

The module introduces the concepts of web design, with a focus on designing responsive websites that are targeted at mobile platforms. Students are introduced to HTML, CSS and JavaScript to provide them with an understanding of what goes into the front-end of modern websites. Using a series of case studies, students will analyse the design and layout of a range of existing sites using a number of common analysis techniques.

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.

This module provides an understanding of why cyber security matters to businesses, to society and to individuals, coupled with knowledge of basic concepts, attack techniques, attacker types, and the core elements of cyber assurance.

This module provides an introduction to the artificial intelligence and data science fields, covering the history of the discipline, and exploring a variety of “classical AI” topics.

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. 

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.

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 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.

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. 

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.

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.

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.

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.

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.

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WHY SUFFOLK

16th place in the Whatuni Student Choice Awards for Best Facilities 2023

WUSCA 2023

5th place in the Whatuni Student Choice Awards for Career Prospects 2023

WUSCA 2023

14th place in the Whatuni Student Choice Awards for Student Support 2023

WUSCA 2023
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Student at The DigiTech Centre
Three students gaming in classroom
Computing students
Two students working at a computer
Students at The DigiTech Centre
Logo of the DigiTech Centre on wall
Inside The DigiTech Centre

Entry Requirements

Entry Requirements

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Career Opportunities

Upon graduation from this degree, students can progress into a range of roles, including:

  • Cyber Security Expert

  • Web Developer

  • Data Scientist

  • Artificial Intelligence Expert

  • Mobile App Developer

  • QA Engineer

  • Network Engineer

  • Software Developer

  • Data Analyst

 

All graduates will also have the opportunity to start their own business within the University of Suffolk Innovation Centre (IWIC). Here, students will have access to hot desk space, networking and collaborative opportunities.

Your Course Team

Ali Alhaj

Ali Alhaj joined the University in July 2020 and is a Lecturer of Cyber Security and course leader of BSc (Hons) Computing.

Ali Alhaj staff profile photo

Associate Professor Sean Preston

Sean Preston is an Associate Professor in Computing and the Associate Dean for Learning, Teaching and Student Experience for the School of Technology, Business.

Sean Preston staff profile photo

Dr Felix Ngobigha

Dr Felix Ngobigha is a Senior Lecturer in Network Engineering and had previously been Scientific Officer with the Centre for Satellite Technology Development.

Felix Ngobigha staff profile photo

Mark Power

At Suffolk, Mark is a Lecturer in Computing and teaches on the BSc (Hons) Computing Degree. Prior to that he worked for a FTSE100 company in telecoms.

Mark Power staff profile photo

Steven Harris

Steve maintains an active interest in 'serious games' including, gaming for the visually impaired and early years educational games.

Steven Harris staff profile photo

Professor Nicholas Caldwell

Professor Nicholas Caldwell is Professor of Information Systems Engineering at the University of Suffolk.

Nicholas Caldwell staff profile photo

Dr Kakia Chatsiou

Kakia is a Lecturer in Computing with expertise in machine learning, information management systems and data science.

Kakia Chatsiou staff profile photo

Dr Chris Lewington

Dr Chris Lewington is a Senior Lecturer in Cyber Security, joining us in June 2019 after a successful career in finance, telecoms, defence and biotechnology.

Dr Adnane Ez-zizi

Dr Adnane Ez-zizi is a Senior Lecturer in Artificial Intelligence and Course Leader for the MSc Data Science and Artificial Intelligence.

Adnane Ez-Zizi staff profile photo

Fees and Funding

UK Full-time Tuition Fee

£9,250

per year
UK Part-time Tuition Fee

£1,454*

per 20 credit module
International Full-time Tuition Fee

£15,210

per year

*Please contact the Student Centre for further details

The decision to study a degree is an investment into your future, there are various means of support available to you in order to help fund your tuition fees and living costs. You can apply for funding from the Spring before your course starts.

UK Fees and Finance UK Bursaries and Scholarships International Fees and Scholarships

Fees and Funding

UK Full-time Tuition Fee*

£9,250

per year
UK Part-time Tuition Fee*

£1,454*

per 20 credit module

* Maximum tuition fees chargeable to Home-fee students are set by the UK Government normally in the autumn or early winter in the year prior to the year of entry (e.g. autumn 2024 for entry in 2025/26). The University of Suffolk reserves the right to increase tuition fees for 2025/26 if the UK Government increases the maximum annual fee. International tuition fees for 2025/26 will be confirmed and updated here in May 2024.

The decision to study a degree is an investment into your future, there are various means of support available to you in order to help fund your tuition fees and living costs. You can apply for funding from the Spring before your course starts.

UK Fees and Finance UK Bursaries and Scholarships International Fees and Scholarships

Ipswich Award

The University of Suffolk is offering a £1,000 Award for students joining the University of Suffolk’s Ipswich campus. The Award is based on specific eligibility criteria based on your year of entry.

More information
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How to Apply

To study this course on a full-time basis, you can apply through UCAS. As well as providing your academic qualifications, you’ll be able to showcase your skills, qualities and passion for the subject.

Apply Now Further Information on Applying
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Karina Karushkova, BSc (Hons) Computing graduate

"The University has a high reputation within the fields of technology especially in relation to the degrees it offers for programming and system design."

read more
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