Computer Science (with Industrial Placement)

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
Systems Engineering and Project Management
Cloud and Distributed Architecture and Security
Data Structures and Algorithms
Machine Learning
Secure Software Development

YEAR 3 (INDUSTRIAL PLACEMENT)
The placement year will take place during the third academic year. This pivotal phase in your education allows you to gain hands-on experience in your field of study, bridging the gap between theoretical knowledge and practical application. It is an opportunity to immerse yourself in a professional environment, develop industry-specific skills, and build a network of contacts that can be invaluable for your future career. During this year, you'll work with professionals, tackle real-world challenges, and refine your understanding of the industry, all while earning academic credit. This blend of academic and professional development is designed to enhance your employability, giving you a competitive edge in the job market upon graduation.

YEAR 4 (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
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

The computing program suite employs a diverse range of cutting-edge industry tools and software, complemented by innovative teaching methods. This dynamic approach not only imparts industry-relevant skills but also empowers you to elevate your work to new heights when possible. The entire staff enthusiastically embraces the active learning framework (ALF), resulting in numerous enhancements to the teaching and learning experience.

Assessment

Assessments in computer science at the university level are designed to evaluate your' understanding, application, and proficiency in various aspects of the discipline. These 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.

Personalised Support

The department follows a well-established open-door approach, actively interacting with students, alumni, and industry stakeholders. Essential information and communication avenues are facilitated through tools like Teams and Moodle. Additionally, every student is assigned a personal tutor, fostering regular meetings, while additional personalized support is extended to part-time students through the Virtual Learning Environment (VLE).