BSc in Mathematics and Computer Science

3 Years On Campus Bachelors Program

Queens University Belfast

Program Overview

The BSc in Mathematics and Computer Science at Queen’s University Belfast is a three‑year degree that blends rigorous mathematical reasoning with practical computing and software development skills. It’s perfect for students who enjoy solving logical problems, writing code, and applying computational thinking to challenges in technology, engineering, science, and data‑driven industries.

Curriculum Structure

Year 1
In the first year, students establish strong foundations in both mathematics and computer science, tackling modules like Mathematical Reasoning and Introduction to Algebra and Analysis to build analytical skills, while Algorithmic Thinking and Introduction to Programming introduce essential coding concepts and problem‑solving in software contexts. This integrated approach ensures students are comfortable with both numerical reasoning and computational logic from the start.

Year 2
During the second year, students expand their mathematical depth with topics such as Linear Algebra and Statistics, while in computer science they engage with core programming concepts, data structures, and software design principles. Modules such as Databases and Information Systems or Object‑Oriented Programming allow students to apply computational approaches to structured data, equipping them for complex problem solving across disciplines.

Year 3
In the final year, students focus on advanced topics like Algorithms and Complexity to understand efficient computation, and Software Engineering to design, build and test robust applications. The year culminates in a substantial Team Project in Mathematics and Computer Science, where students work collaboratively to deliver a significant software or mathematical modelling solution, integrating their interdisciplinary knowledge into a real‑world‑style project.

Focus Areas
Mathematical reasoning and modelling, algorithm design and analysis, software development and engineering, data structures and databases, computational problem solving, team‑based project implementation.

Learning Outcomes
Students will be able to apply mathematical and computational techniques to solve technical problems, design and analyse algorithms, develop software solutions using modern paradigms, interpret complex data, think critically and communicate technical ideas effectively, and collaborate professionally on substantial projects.

Professional Alignment (Accreditation)
This degree is awarded by Queen’s University Belfast under recognised UK academic standards, providing graduates with a respected qualification that prepares them for careers in technology, engineering, finance, data science, and further postgraduate study.

Reputation (Employability Rankings)
Queen’s University Belfast is part of the Russell Group of research‑intensive UK universities, known for strong outcomes in STEM disciplines, with graduates in mathematics and computing sectors highly sought after by employers in industry and research.

Experiential Learning (Research, Projects, Internships etc.)

The BSc in Mathematics and Computer Science at Queen’s University Belfast offers students an education where theory meets hands‑on practice. Learners study in modern teaching facilities with specialised computer labs designed for programming, algorithm testing and computational mathematics. Throughout the degree, students build practical coding experience using industry‑relevant languages and tools, engaging in computer‑based modules that integrate mathematics with computing. Small‑group tutorials and workshop sessions encourage collaboration and deepen technical confidence. In final year, students complete a substantial project that requires them to apply mathematical reasoning and computing techniques to solve complex problems. Additionally, students can opt for an industry placement year to apply their skills in professional settings, strengthening their readiness for the job market and boosting career outcomes:

Regular use of programming languages and computational tools in practical labs to reinforce learning.
Access to dedicated computing facilities that support software development, algorithm analysis and simulations.
Team‑based assignments that foster collaboration, communication and project management.
Supervised final‑year project integrating mathematics and computer science in a real‑world‑style challenge.
Optional year in industry placement to gain professional experience and apply academic skills in a workplace environment.
Workshops and tutorials designed to build confidence in problem solving and technical communication.

Programme Overview
This three‑year single honours degree blends core mathematical theory with foundational and advanced computer science topics. Students explore key areas such as programming, algorithms, data structures, discrete mathematics and computational modelling. The curriculum is designed so that students develop both analytical reasoning and practical computing capabilities, giving them the confidence to pursue roles that demand quantitative problem solving and software development skills.

Practical Skills and Tools
Throughout the degree, students build competencies that are highly valued in technology and analytical roles:

Solid grounding in programming languages and computational thinking.
Mathematical modelling and analytical problem‑solving techniques.
Understanding of core computer science principles, data structures and algorithms.
Practical experience with software tools used in computing and applied mathematics.
Teamwork, project planning and effective technical communication through group assignments.

Career and Progression Opportunities
Graduates from this programme are well placed for careers in software development, data science, systems analysis, technology consultancy and related fields where combined mathematical insight and computing ability are essential. Many students also pursue further study or professional qualifications in advanced computing, machine learning, artificial intelligence or applied mathematics.

Why This Matters
By combining rigorous mathematical training with practical computing experience, the BSc in Mathematics and Computer Science at Queen’s University Belfast prepares students not just to graduate, but to thrive in careers where analytical thinking, technical proficiency and adaptable problem solving make a real impact.

Progression & Future Opportunities

Graduates of the BSc Mathematics and Computer Science programme at Queen’s University Belfast are equipped for careers at the intersection of mathematics, computation, and data analysis: typical roles include Software Engineer, Data Scientist, Quantitative Analyst, and Systems Analyst. The programme combines rigorous mathematical training with practical computer science skills, preparing graduates for roles in technology, finance, and research sectors.

Progression & Future Opportunities

Support from Queen’s Careers, Employability & Skills, including personalised career consultations, CV and interview guidance, employer networking events, and access to job opportunities across technology and analytical industries.
Strong employment outcomes: around 87 % of mathematics and computing graduates are in employment or further study within 15 months of graduation.
Competitive earning potential: graduates from numerate and computing disciplines typically achieve higher-than-average starting salaries in professional roles.
Industry engagement: opportunities for year-in-industry placements and collaboration with technology and finance companies, enhancing practical experience and employability.
Degree credibility: awarded by a Russell Group research-led university, offering long-term recognition and professional value.

Further Academic Progression
Graduates can continue their studies through Master’s or PhD programmes in areas such as Computer Science, Data Science, Artificial Intelligence, or Applied Mathematics, leveraging the strong computational and analytical foundation developed during the BSc programme.