School of Computer Science BCS accreditation 2021 - 2026

Artificial Intelligence MEng (Hons) - 2.2.2 Evaluate systems in terms of quality and trade-offs

COMP10120 First Year Team Project

Students work through alternative designs and approaches to their system with their tutor

Assesement : Group coursework, Presentation

COMP11120 Mathematical Techniques for Computer Science

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

Assesement : Examination, Individual coursework

COMP11212 Fundamentals of Computation

The unit focuses on a number of equivalent formalisms (regular expressions and various flavours of automata). Trade-offs between these systems are discussed in terms of their usability, implementation and reasoning about their properties.

Assesement : Not Assessed

COMP13212 Data Science

The course covers topics relevant to objective evaluation of systems: concept and quantification of uncertainty in measured and experimental data, visualization of data, hypothesis generation and testing, and basic statistical tests. These topics constitute a substantial part of the course. One objective of the course is that on successful completion, the student should be able to design and carry out a valid experiment to test a hypothesis.

Assesement : Examination, Lab work

COMP15111 Fundamentals of Computer Architecture

Some basic tradeoffs in terms of execution speed and storage are explained

Assesement : Individual coursework

COMP15212 Operating Systems

Explicitly analyses different algorithms for various OS components, e.g. caching and scheduling strategies

Assesement : Examination, Individual coursework

COMP16412 Introduction to Programming 2

Pros and cons of different algorithmic and design approaches

Assesement : Exams, Coursework

COMP23311 Software Engineering 1

The quality of the system students build is assessed in using test code quality and test coverage tool, continuous integration and testing tools

Assesement : Group coursework

COMP24112 Machine Learning

This course requires learning outcome on discussing the differences (including limitations and advantages, quality and trade-offs) between different machine learning models.

Assesement : Examination

COMP24412 Knowledge Based AI

Different reasoning systems are evaluated for the appropriateness in different scenarios.

Assesement : Lab work

COMP26020 Programming Languages & Paradigms

A range of trade-offs in terms of designing, building, compiling programs are discussed throughout the course unit

Assesement : Examination, Individual coursework

COMP26120 Algorithms and Data Structures

Analysing and understanding performance trade-offs is a core component of lab work.

Assesement : Lab work

COMP30040 Third Year Project Laboratory

Students are expected to evaluate alternative solutions in their work and to reflect on their completed work.

Assesement : Individual coursework