Computer Science

Why choose this course?
Our BSc Computer Science course offers a solid foundation in core computer science principles, programming, and software development, with opportunities to specialise in Machine Learning,  AI and Data Analytics. This course will allow you to develop vital ethical, professional, and communication skills to excel in a rewarding IT career.

You will:
Gain hands-on experience through lab work and coding assignments
Utilise cutting-edge industry tools and software
Study in state-of-the-art facilities, including our Cyber Innovation Academy
Learn from experienced professionals and experts in the field
Engage in active learning sessions, industry talks, workshops, and practical exercises
Have the opportunity to qualify for CISCO accreditation upon course completion

Key Course Features:
The curriculum encompasses programming fundamentals, algorithms, data structures, and agile methodologies, with a focus on problem-solving, teamwork, and ethical considerations, preparing you for sustainable and innovative practices in digital technology
Gain practical, hands-on experience in advanced fields such as Machine Learning, Artificial Intelligence (AI), and Data Analytics
The course integrates core project modules simulating cross-disciplinary industry practices with subject-specific modules, offering theoretical and practical expertise
This course embraces the Active Learning Framework (ALF), enhancing the teaching and learning experience through diverse, dynamic teaching methods

What you will study
YEAR 1 (LEVEL 4)
The first year (Level 4) establishes a solid foundation in software and web development within the broader context of computing and digital industries. Through design exercises, case studies, and projects, you will gain practical experience by applying core principles to real-world scenarios.

MODULES
Programming Fundamentals
Computer Systems and Architecture
Information Security and Governance
Applied Computational Methods
Software Development Methodologies
Fundamentals of Machine Learning

YEAR 2 (LEVEL 5)
In your second year (Level 5), you will explore advanced principles in software and web design, development, and production, with a focus on practical application through case studies, teamwork, and design exercises. You will enhance your understanding of industry tools, workflows, and roles, while developing problem-solving skills using data structures and algorithms to deliver innovative solutions. This year also sharpens your collaboration, communication, and project management abilities, alongside fostering professional practices and reflection on social, ethical, and sustainability issues—preparing you for academic success and a competitive edge in your professional career.

MODULES
Group Project: This module offers essential industry-simulated experience, equipping you to manage tasks, challenges, and scenarios encountered in real-world, group-based digital projects. You will develop skills in organisation, communication, and coordination while focusing on the design, development, and implementation of a digital product aligned with professional methodologies and real-world contexts.
Systems Engineering and Project Management
Cloud and Distributed Architecture and Security
Data Structures and Algorithms
Machine Learning
Secure Software Development

YEAR 3 (LEVEL 6)
The final year (Level 6) emphasises critically evaluating computing within a broader context, focusing on advanced principles in software/web design, development, and production through graduate-level projects. You will apply development tools, considering technical, design, and team-based skills, while addressing social, ethical, and sustainability issues. The year fosters advanced competencies in research, programming, and software systems development, including security techniques and specialisation in computer science. You will refine problem-solving, communication, leadership, and agile project management skills. Additionally, you will enhance personal growth, time management, and research abilities, preparing you for professional success in the computing industry.

MODULES
Project: The project module is designed to prepare you for the tasks and challenges that you may encounter in the workplace after your graduation. Its objectives are to equip you with the skills to independently plan, manage, and report on a substantial, long-term project; apply theoretical knowledge from taught modules to practical, real-world problems; and critically evaluate diverse and often conflicting information from manuals, books, and research journals. Additionally, the project offers an opportunity to specialise in an area aligned with your personal interests and degree program, enhancing your expertise and career readiness.
Cryptography and Defensive Systems
Deep Learning Implementation
Emergent Technologies
Data Analysis and Visualisation

The information listed in this section is an overview of the academic content of the programme that will take the form of either core or option modules. Modules are designated as core or option in accordance with professional body requirements and internal academic framework review, so may be subject to change.

Teaching & Assessment
Teaching

This course leverages cutting-edge industry tools and software, paired with innovative teaching methods, to equip students with industry-relevant skills and empower them to excel. Staff fully embrace the Active Learning Framework (ALF), enhancing the teaching and learning experience through diverse, dynamic methods.

The programme integrates core project modules simulating cross-disciplinary industry practices with subject-specific modules, offering theoretical and practical expertise. Students engage in active learning sessions, industry talks, workshops, and practical exercises while exploring emerging technologies and industry best practices.

Most undergraduate modules, apart from the 40-credit final-year project, are 20 credits. Each 20-credit module requires 200 hours of learning, consisting of a small proportion of timetabled sessions, including lectures, labs, workshops, and tutorials, alongside a significant proportion of guided independent study. Staff operate an Open-Door policy, providing flexible support beyond scheduled hours.

Assessment

Aligned with the Active Learning Framework (ALF), the programmes employ innovative, context-driven assessment strategies that integrate portfolio-building exercises to enhance student achievement and employability. Cloud-based systems track and manage student progress in projects, ensuring transparency in group work and simulating an industry environment to deepen professional awareness.

Assessments focus on mastery of skills and knowledge, adopting a tailored approach supported by formative activities such as self-reflection, peer assessments, and targeted feedback. For coursework and portfolio-based modules, milestone reviews provide personalised feedback, keeping students on track to meet learning outcomes and deliverables.

Modules with embedded industry certifications include preparatory coursework submissions for feedback, ensuring readiness for final assessments. These assessments align with certification requirements and may involve remote proctored in-class evaluations, bridging academic and industry standards to strengthen student employability.

Assessments encompass a diverse range of methods, including:

Coursework and Projects: Assignments and projects provide hands-on experience, allowing you to apply theoretical knowledge to real-world scenarios. This may include software development projects, research papers, or problem-solving tasks.
Coding Assignments: Practical coding assignments assess your programming skills, logical reasoning, and ability to develop efficient and effective code.
Group Projects: Collaborative projects evaluate teamwork, communication, and the ability to work in diverse teams, reflecting the collaborative nature of the tech industry.
Presentations: You may be required to present your findings, solutions, or project outcomes, enhancing your communication and presentation skills.
Laboratory Work: Practical sessions in computer labs assess your' ability to apply concepts, troubleshoot issues, and work with various tools and technologies.
Problem-solving Exercises: These exercises challenge you to solve complex problems, encouraging critical thinking and analytical skills.
Reports and Documentation: Writing reports or documenting project processes assesses your ability to communicate technical information clearly and concisely.