School of Computer Science BCS accreditation 2021 - 2026

Artificial Intelligence MEng (Hons) - COMP11120 Mathematical Techniques for Computer Science

2.1.1 Knowledge and understanding of facts, concepts, principles & theories

It teaches areas of mathematics required for various fields of computer science in the form of the concept of proof, formal logic, probability, recursion and induction, relations, and linear algebra.

Assesement : Examination, Individual coursework

2.1.2 Use of such knowledge in modelling and design

It provides a basis for reasoning about such systems and their properties, introduces notions that underpin the use of probabilities in modelling various situations, and gives the students additional abstract tools to apply when it comes to understanding the behaviour of such systems.

Assesement : Examination, Individual coursework

2.1.3 Problem solving strategies

The students practice problem solving by addressing exercises. Some of the exercises and the examples on this course particularly address the application of mathematical concepts and principles to problems from computer science.

Assesement : Examination, Individual coursework

2.1.4 Analyse if/how a system meets current and future requirements

It enables students to use logic to establish such criteria formally and it provides examples fo how to give proofs of such properties.

Assesement : Examination, Individual coursework

2.1.5 Deploy theory in design, implementation and evaluation of systems

The unit teaches the mathematics underpinning the formal side of specifying such systems.

Assesement : Examination, Individual coursework

2.2.2 Evaluate systems in terms of quality and trade-offs

The unit lays the mathematical groundwork for the notions related to algorithmic complexity.

Assesement : Examination, Individual coursework

2.3.2 Development of general transferable skills

On this unit the students learn to think abstractly. They have to write down their solutions to problems in such a way that another person may understand them.

Assesement : Examination, Individual coursework

3.1.2 Methods, techniques and tools for information modelling, management and security

The units teaches the mathematical underpinnings for some of that modelling, for example in the form of probability theory and logic.

Assesement : Examination, Individual coursework

3.1.4 Knowledge and understanding of mathematical and/or statistical principles

The course consists of teaching such mathematical principles.

Assesement : Examination, Individual coursework

3.2.1 Specify, deploy, verify and maintain information systems

The unit provides tools for these processes, for example in the form of logic and probability theory.

Assesement : Examination, Individual coursework

3.2.3 System Design

Students learn to design systems using UML class diagrams that include object oriented features. During workshops students model parts of the tree of life to design systems that use inheritance and interfaces. In another practical workshop they reverse engineer the hierarchical components of a JavaFX application to extract its design from a snapshot.

Assesement : formative assessment in labs, workshops and coursework; summative assessment in coursework and exam

4.1.1 Knowledge and understanding of scientific and engineering principles

The course teaches relevant principles of mathematics that are the basis for such principles.

Assesement : Examination, Individual coursework

4.1.2 Knowledge and understanding of mathematical principles

The course consists of teaching such mathematical principles.

Assesement : Examination, Individual coursework

4.1.3 Knowledge and understanding of computational modelling

The course teaches in particular probability theory which is relevant to such modelling.

Assesement : Examination, Individual coursework

4.2.1 Specify, deploy, verify and maintain computer-based systems

The course teaches logic and probability theory, both of which are ingredients for these processes.

Assesement : Examination, Individual coursework