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2023/24 Undergraduate Module Catalogue
COMP1511 Introduction to Discrete Mathematics
10 creditsClass Size: 500
Module manager: Prof Kristina Vuskovic
Email: k.vuskovic@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2023/24
This module is not approved as a discovery module
Module summary
Discrete mathematics studies finite mathematical structures and is the mathematical foundation for many Computer Science disciplines including algorithm design, data structures, database theory, formal languages and automata, compilers and importantly security. This module concentrates on the fundamentals of discrete mathematics introducing a number of concepts and skills that will be applied throughout the remainder of the Computer Science curriculum. This module builds upon previously taught mathematics modules and introduces students to a variety of powerful tools that can model a wide range of problems that arise in many areas including transportation, telecommunications and molecular biology.Objectives
To develop the range of concepts and techniques that students have when approaching real world problems and to allow students the opportunity to apply problem solving techniques to problems that arise in Computer Science disciplines. To prepare students for further mathematical study in the discipline of Computer Science.Learning outcomes
On successful completion of this module a student will have demonstrated the ability to:
- apply counting arguments to problems that arise in Computer Science and more widely.
- recall definitions and theorems from the topic areas of combinatorics, discrete probability and graph theory.
- construct mathematical arguments, in the effort to prove the correctness of theorems.
- deploy problem solving techniques to problems within the discipline.
- transfer problem solving skills into difference domains.
Syllabus
This module covers the following 3 topic areas:
- Combinatorics: multiplication principle, addition principle, Pigeonhole principle, permutation and combinations (with and without repetition).
- Discrete probability: experiment, sample space, events, finite probability space, equi-probable spaces, conditional probability, mutually exclusive and independent events.
- Graph theory: graph models, graph isomorphism, degree, paths, cycles, Euler's theorem, bipartite graphs and trees.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Lecture | 22 | 1.00 | 22.00 |
| Tutorial | 10 | 1.00 | 10.00 |
| Private study hours | 68.00 | ||
| Total Contact hours | 32.00 | ||
| Total hours (100hr per 10 credits) | 100.00 | ||
Opportunities for Formative Feedback
Attendance and formative assessmentMethods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| In-course Assessment | Coursework 1 | 5.00 |
| In-course Assessment | Coursework 2 | 5.00 |
| In-course Assessment | Coursework 3 | 5.00 |
| In-course Assessment | Coursework 4 | 5.00 |
| Total percentage (Assessment Coursework) | 20.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Exams
| Exam type | Exam duration | % of formal assessment |
| Standard exam (closed essays, MCQs etc) (S1) | 2 hr 00 mins | 80.00 |
| Total percentage (Assessment Exams) | 80.00 | |
This module will be reassessed by examination only
Reading list
The reading list is available from the Library websiteLast updated: 26/09/2023
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