Undergraduate Programme and Module Handbook 2026-2027
Module COMP1021: Mathematics for Computer Science
Department: Computer Science
COMP1021: Mathematics for Computer Science
| Type | Open | Level | 1 | Credits | 20 | Availability | Available in 2026/2027 | Module Cap | Location | Durham |
|---|
Prerequisites
- A-level Mathematics (or equivalent) Grade A.
Corequisites
- COMP1051 Computational Thinking
Excluded Combination of Modules
- MATH1061 Calculus
- MATH1071 Linear Algebra I
- MATH1551 Maths for Engineers and Scientists
- MATH1571 Single Maths B
- MATH1597 Probability I
Aims
- To introduce students to fundamental concepts from linear algebra, calculus, probability and mathematics that are necessary for and relevant to modern Computer Science.
- To introduce students to the application of linear algebra, calculus, probability and mathematics to topics within mainstream Computer Science.
Content
- Sets, functions and relations
- Matrices and linear systems
- Vector spaces, linear dependence, basis and dimension
- Linear transformations, eigenvectors and eigenvalues
- Matrix decompositions
- Multivariate functions
- Partial differentiation
- Fourier Transforms
- Probability and statistics
Learning Outcomes
Subject-specific Knowledge:
- On completion of the module, students will be able to demonstrate:
- an understanding of the fundamental notions from linear algebra, calculus and mathematics and their relevance to mainstream Computer Science.
- an understanding of core concepts in probability and statistics.
- an understanding of mathematical notation.
Subject-specific Skills:
- On completion of the module, students will be able to demonstrate:
- an ability to apply methods and techniques from linear algebra, calculus and mathematics.
- an ability to reason with probability and apply methods of statistics.
- an ability to use mathematical notation.
Key Skills:
- On completion of the module, students will be able to demonstrate:
- an ability to apply mathematical reasoning to practical scenarios.
- an ability to formalise general arguments.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures enable the students to learn new material relevant to linear algebra, calculus and mathematics, as well as their applications in Computer Science.
- Problem classes enable the students to put into practice learning from lectures and strengthen their understanding through application.
- Formative and summative assessments assess the application of methods and techniques, and examinations in addition assess an understanding of core concepts.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 44 | 2 per week | 1 hour | 44 | |
| Problem Classes | 21 | 1 per week | 2 hours | 42 | Yes ■ |
| Preparation and Reading | 114 | ||||
| Total | 200 |
Summative Assessment
| Component: Examination | Component Weighting: 66% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| On Campus Written Examination | 2 hours | 100% | |
| Component: Coursework | Component Weighting: 34% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| In-Year Test | 100% | ||
Formative Assessment:
Example formative exercises are given during the course. Additional revision lectures may be arranged in the module's lecture slots in the 3rd term.
■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.