2020/21 Undergraduate Module Catalogue

COMP1511 Introduction to Discrete Mathematics

10 creditsClass Size: 500

Module manager: Kristina Vuskovic
Email: k.vuskovic@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2020/21

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, Pigeon hole 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
Class tests, exams and assessment	1	2.00	2.00
Lecture	22	1.00	22.00
Tutorial	10	1.00	10.00
Private study hours			66.00
Total Contact hours			34.00
Total hours (100hr per 10 credits)			100.00

Private study

Taught session preparation: 18 hours
Taught session follow-up: 18 hours
Self-directed study: 7 hours
Assessment activities: 23 hours

Opportunities for Formative Feedback

Attendance and formative assessment

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
In-course Assessment	Coursework 1 (Gradescope)	10.00
In-course Assessment	Coursework 2 (Gradescope)	10.00
In-course Assessment	Coursework 3 (Gradescope)	10.00
In-course Assessment	Coursework 4 (Gradescope)	10.00
Total percentage (Assessment Coursework)		40.00

This module will be reassessed by an online time-constrained assessment.

Exams

Exam type	Exam duration	% of formal assessment
Online Time-Limited assessment	48 hr 00 mins	60.00
Total percentage (Assessment Exams)		60.00

This module will be reassessed by an online time-constrained assessment.

Reading list

The reading list is available from the Library website

Last updated: 29/01/2021 15:43:24

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