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BSc Computer Science and Mathematics / Course details

Year of entry: 2021

Course description

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1st Year Team Projects - Computer Science UoM

Choosing the Computer Science and Mathematics programme allows you to combine the study of these two disciplines, each occupying half of your studies, and explores the reliance of each on the other.

This joint honours degree programme enables you to acquire a useful combination of mathematical and computer science knowledge and skills. It covers the knowledge needed to implement mathematical models in simulations that evaluate real world situations such as stress analysis in bridges and buildings, airflow over aircraft wings, or financial modelling.

The topics studied include a number of important ideas of mathematics, including the concepts of rigorous argument, formal proof and the power of abstract formulation of problems. This is combined with the core computer science topics of programming and software engineering, together with the study of mathematical principals underpinning the foundations of computing.

You will gain not only knowledge and practical experience of the latest technologies, but also a grounding in the underlying principles of the subject. It is this combination of skills that enable our graduates to keep pace with this fast moving subject, and secure top jobs in industry and research.

Special features

Dr Andrea Schalk, Computer Science & Maths programme director

The CS & Maths course has a real sense of community around it, which helps create a culture of students supporting each other.

The course covers exciting areas such as machine learning and data science which are maths heavy, so this enables students to go in careers or further studies in Maths or Computer Science.

Dr Andrea Schalk / Computer Science & Maths Programme Director
  • By drawing staff from two 'excellent' rated departments students are taught by experts in each field.
  • Traditional careers to which both computer science and mathematics graduates progress are open to you.
  • Many of our projects and taught modules are supported by Industry

Teaching and learning

At Manchester you will be taught by academic staff who are leading experts in computer science, in a diverse and inclusive learning environment. Teaching and Learning will be delivered using a variety of methods, including: 

  • Lectures
  • Tutorial classes
  • Practical laboratory sessions
  • Group activities
  • PASS sessions and peer mentoring 

Some activities will be delivered face-to-face and others online, following a blended learning approach.

The course contains strong practical elements: a year-long group project focused on the design and development of a web application in Year 1; development of software engineering skills through engagement with industrial mentors in Year 2; and a year-long individual project in Year 3. Each year aims to progressively build your skills, knowledge, and confidence in practical computer science.

A typical week in your first year of study will comprise 40 hours of activity, of which approximately 20 hours will be timetabled study and 20 hours will be independent or self-directed study. The timetabled study is a mix of practical and theoretical sessions.

As you progress through the course an increasing emphasis will be placed on independent study, and this reflects you applying your knowledge and skills in substantial individual and group projects. In your third year of study, between 25 and 30 hours each week will typically be independent study. You will be supported by staff through all of your independent study, and this transition to being able to explore your own ideas through project work is an important attribute of a graduate computer scientist. 

PASS (Peer Assisted Study Sessions) and Peer Mentoring  

We're proud of our innovative PASS (Peer Assisted Study Sessions) and Peer Mentoring scheme. The PASS scheme provides additional support around the current week's tutorial. It's entirely voluntary and consists of second, third and fourth-year current students helping first years to tackle problems defined by the content of the current tutorial. The emphasis is on showing students how to think about the problems, how to develop problem-solving skills and how to get the most from the educational resources available.   

More about blended learning

Some of your activity will be synchronous, where you learn live with your lecturer / peers and can interact as appropriate, helping you get support and feel part of a community. At other times it will be asynchronous, where you access materials like presentations, video content, online discussion boards or collaborative documents in your own time (within a framework provided by your programme).   

We believe this blended approach will help each individual study in a way that works best for them and will ensure students receive the best student-experience.

Coursework and assessment

The course is assessed by a variety of methods, each appropriate to the topic being assessed. These methods include practical exercises, presentations, practical demonstrations, and written and online examinations. You will also have opportunities to monitor your progress using online quizzes and tutorial exercises. 

Course content for year 1

Course units for year 1

The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.

TitleCodeCredit ratingMandatory/optional
First Year Team Project COMP10120 20 Mandatory
Introduction to Programming 1 COMP16321 20 Mandatory
Introduction to Programming 2 COMP16412 10 Mandatory
Foundations of Pure Mathematics B MATH10111 15 Mandatory
Calculus and Vectors B MATH10131 15 Mandatory
Linear Algebra B MATH10212 15 Mandatory
Calculus and Applications B MATH10232 15 Mandatory
Fundamentals of Computation COMP11212 10 Optional
Data Science COMP13212 10 Optional
Operating Systems COMP15212 10 Optional

Course content for year 2

Course units for year 2

The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.

TitleCodeCredit ratingMandatory/optional
Real Analysis B MATH20111 10 Mandatory
Algebraic Structures 1 MATH20201 10 Mandatory
Logic and Modelling COMP21111 10 Optional
Database Systems COMP23111 10 Optional
Software Engineering 1 COMP23311 10 Optional
Software Engineering 2 COMP23412 10 Optional
Introduction to AI COMP24011 10 Optional
Machine Learning COMP24112 10 Optional
Knowledge Based AI COMP24412 10 Optional
Programming Languages & Paradigms COMP26020 20 Optional
Algorithms and Data Structures COMP26120 20 Optional
Introduction to Visual Computing COMP27112 10 Optional
Distributed Systems COMP28112 10 Optional
Probability 1 MATH10141 10 Optional
Metric Spaces MATH20122 10 Optional
Algebraic Structures 2 MATH20212 10 Optional
Introduction to Logic MATH20302 10 Optional
Partial Differential Equations and Vector Calculus B MATH20411 10 Optional
Fluid Mechanics MATH20502 10 Optional
Classical Mechanics MATH20512 10 Optional
Numerical Analysis 1 MATH20602 10 Optional
Discrete Mathematics MATH20902 10 Optional
Introduction to Financial Mathematics MATH20912 10 Optional
2P2: Complex Analysis MATH29142 10 Optional
Displaying 10 of 24 course units for year 2

Course content for year 3

Course units for year 3

The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.

TitleCodeCredit ratingMandatory/optional
Third Year Project Laboratory COMP30030 30 Mandatory
Giving Meaning to Programs COMP31311 10 Optional
Agile Software Pipelines COMP33312 10 Optional
User Experience COMP33511 10 Optional
AI and Games COMP34111 10 Optional
Cognitive Robotics COMP34212 10 Optional
Computational Game Theory COMP34612 10 Optional
Natural Language Processing COMP34711 10 Optional
Natural Language Understanding COMP34812 10 Optional
Algorithms and Complexity COMP36111 10 Optional
Mathematical Systems and Computation COMP36212 10 Optional
Graphics & Virtual Environments COMP37111 10 Optional
Computer Vision COMP37212 10 Optional
Advanced Distributed Systems COMP38311 10 Optional
Cyber Security COMP38412 10 Optional
Quantum Computing COMP39112 10 Optional
Mathematics Education MATH30002 10 Optional
Fractal Geometry MATH31042 10 Optional
Topology MATH31052 10 Optional
Group Theory MATH32001 10 Optional
Commutative Algebra MATH32012 10 Optional
Coding Theory MATH32032 10 Optional
Hyperbolic Geometry MATH32051 10 Optional
Algebraic Geometry MATH32062 10 Optional
Number Theory MATH32072 10 Optional
Combinatorics and Graph Theory MATH32091 10 Optional
Mathematical Logic MATH33011 10 Optional
Complex Analysis and Applications MATH34001 20 Optional
Wave Motion MATH35012 10 Optional
Mathematical Biology MATH35032 10 Optional
Symmetry in Geometry and Nature MATH35082 10 Optional
Matrix Analysis MATH36001 10 Optional
Numerical Analysis 2 MATH36022 10 Optional
Problem Solving by Computer MATH36031 10 Optional
Convex Optimization MATH36062 10 Optional
Mathematical Modelling in Finance MATH39032 10 Optional
Displaying 10 of 36 course units for year 3

Scholarships and bursaries

The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.

For information about scholarships and bursaries please visit our  undergraduate student finance pages .

What our students say

Student ambassadors
Student ambassadors working at an Open Day
Todd Davies, BSc Computer Science

I always has the mind-set in my degree that I was learning how to learn. I feel like the BSc in Computer Science gives you a very holistic view of the subject, all the way from logic gates to high-level modules like Computer Vision.

Seb Masaru, BSc Computer Science

The community, the Department, the University, and the city itself are so vibrant in Manchester. You get the sensation that the people here are all extremely approachable.

Facilities

Students working in the Collabs, Kilburn Building
Students working in the Collabs, Kilburn Building

As you would expect from leaders in the field, we offer some of the most up to date facilities in the world. Amongst the wide range of facilities available to you are:

  • Newly refurbished computing labs furnished with modern desktop computers, available with Linux and Windows
  • Access to world leading academic staff
  • Collaborative working labs complete with specialist computing and audio visual equipment to support group working.
  • Over 300 Computers in the Department dedicated exclusively for the use of our students.
  • Access to a hardware library, with top of the range equipment, including drones, robots and oculus rifts.

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk