Program Overview
Algorithms (COMP0005)
Key Information
The module is part of the Faculty of Engineering Sciences, specifically the Computer Science department, and carries a credit value of 15. Restrictions apply, with module delivery available for UG (FHEQ Level 4) on specific programs such as BSc Computer Science, MEng Computer Science, MEng Mathematical Computation, and BA Philosophy and Computer Science.
Alternative Credit Options
There are no alternative credit options available for this module.
Description
Aims
The aim of this module is to introduce students to fundamental data structures and algorithms, providing a basis for programming and understanding computation. It applies these techniques to computational problems to develop problem-solving skills, analyze algorithm efficiency, and encourage thoughtful approaches to computational problem analysis and design.
Intended Learning Outcomes
On successful completion, a student will be able to:
- Understand and effectively use various fundamental data structures in algorithm design and implementation.
- Comprehend fundamental algorithmic problems and their solving algorithms.
- Analyze the space and time efficiency of algorithms and design efficient ones.
Indicative Content
The module typically covers:
- Analysis of algorithms
- Abstract Data Types
- Sorting Algorithms
- Searching Algorithms
- Graphs Algorithms
- String-processing Algorithms
Requisites
To be eligible, a student must be registered on a program for which the module is formally available. Basic experience with Python programming is expected, with resources for self-study and Programming Tutor support provided in advance.
Module Deliveries for 2026/27 Academic Year
The intended teaching term is Term 2 for Undergraduate (FHEQ Level 4) students.
Teaching and Assessment
Mode of Study
The module is taught in person.
Methods of Assessment
- 80% Exam
- 20% Group activity
Mark Scheme
Numeric Marks are used.
Other Information
- The number of students on the module in the previous year was 221.
- The module leader is Professor James Brotherston.
Last Updated
This module description was last updated on 10th March 2026.