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Unit information: Topics in Discrete Mathematics 3 in 2018/19

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Unit name Topics in Discrete Mathematics 3
Unit code MATH30002
Credit points 10
Level of study H/6
Teaching block(s) Teaching Block 2C (weeks 13 - 18)
Unit director Dr. Walling
Open unit status Not open

Students must have taken at least two of the following units: MATH20200 (Metric Spaces), MATH21800 (Algebra 2), MATH21400 (Linear Algebra 2). For joint Mathematics and Computer Science students, it would be desirable to have taken COMS21103 (Data Structures and Algorithms). Students may not take this unit if they have taken the corresponding Level M/7 unit Topics in Discrete Mathematics 34.



School/department School of Mathematics
Faculty Faculty of Science


Unit aims

Ths is a topics course aimed at deepening and broadening the students' knowledge of various aspects of discrete mathematics, as well as illustrating connections between discrete mathematics and other areas such as algebra, probability, number theory, analysis and computer science.

General Description of the Unit

Discrete mathematics refers to the study of mathematical structures that are discrete in nature rather than continuous, for example graphs, lattices, partially ordered sets, designs and codes. It is a classical subject that has become very important in real-world applications, and consequently it is a very active research topic.

This topics course exposes the students to a selection of advanced cutting-edge topics in discrete mathematics.

While results and problems of recent origin may be included in the syllabus, the instructors aim to make the material accessible to all students fulfilling the prerequisites by providing complete lectures notes and including all necessary background material.

The unit is suitable for students with a firm grasp of the basic concepts in the 2nd year combinatorics course, and likely of interest to those with an interest in number theory, algebra, probability and/or theoretical computer science.

Relation to Other Units

The course follows on from Combinatorics and complements Complex Networks and the Data Structures and Algorithms unit in Computer Science.

Intended learning outcomes

Learning Objectives

In accordance with the specific syllabus taught in any particular year, students who successfully complete the unit should:

  • have developed a solid understanding of the advanced concepts covered in the course;
  • be able to use techniques from algebra, analysis and probability to solve problems in discrete mathematics;
  • have a good grasp of the applications of combinatorial techniques in other areas of mathematics and to real-world problems.

Transferable Skills

The ability to think clearly about discrete structures and the ability to analyse complex real-world problems using combinatorial abstractions.

Teaching details

Lectures, including examples and revision classes, supported by lecture notes with problem sets and model solutions. Self-study with directed reading based on recommended material.

Assessment Details

100% Examination.

Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.

Reading and References

Reading and references are available at