CS1AC16-Applications of Computer Science

Module Provider: Computer Science
Number of credits: 20 [10 ECTS credits]
Level:4
Terms in which taught: Autumn / Spring / Summer module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2023/4

Module Convenor: Prof Richard Mitchell
Email: r.j.mitchell@reading.ac.uk

Type of module:

Summary module description:

This module introduces popular applications associated with computers, including artificial intelligence, robotics, virtual reality, computer visionÌýand data analytics.

Aims:

The module aims to broaden students’ knowledge of computer science with applications in key areas to enhance their understanding to the discipline.

This module also encourages students to develop a set of professional skills such as problem solving. Some aspects of social and Legal aspects of artificial intelligence, robotics and vision are considered.

Assessable learning outcomes:
Students completing this module should be able to describe typical techniques and apply relevant algorithms to artificial intelligence and robots, to use basic algorithms describing tasks involved in computer vision and computer graphics; and to deal with data workflows with relevant data analytical tools.

Additional outcomes:

Outline content:

The module consists of four application themes, as listed below:

• Artificial intelligence: here various methods are discussed which are used for ‘intelligent’ computing machines. These include classical AI methods such as Expert Systems and Problem Solving, as well as neural networks and evolutionary computing methods which, have been inspired by natural systems. Applications for artificial intelligence algorithms are also considered;


• Robotics, Artificial Life and Virtual Reality: a cybernetic approach to these subjects is taken, showing how the theme of feedback is key to the control of robots, interaction with robots, computers and humans, and learning by robots and other forms of artificial life. Different types and applications of robots are described, their history given and their brain, sensors and actuators are discussed. Interaction is explored in terms of robots interacting with humans and robots, and humans in Virtual Reality systems, for which computer graphics and haptics are also discussed. Concepts in artificial life are explored, including mobile robots, Game of Life, Daisyworld as well as Fractals and, Lindemayer systems which can be used in virtual worlds;


• Computer vision:Ìý this is the science behind development of capability to emulate (or possibly exceed) human's ability to visually sense the world, and is concerned with the automatic extraction, analysis and understanding of useful information from a single image or multiple images.Ìý This block of lectures will specifically focus on of some of most important methodologies and applications of computer vision and include topics such as biometrics, detection and tracking, deep learning, and behavioural recognition.Ìý The lectures cover both the underpinning theory behind the different topics presented as well as a deeper understanding of how the methods are applied in the real world;


• Data analytics: Students are introduced to the concept of extracting useful information from data, covering types of data, data sources, pre-processing and manipulation techniques, feature selection and transformation, and data visualisation. These concepts are applied with hands-on activities using relevant software.

Brief description of teaching and learning methods:

The module comprises weekly lectures, an online course, associated laboratory practicals, assignments and some revision tutorials. Laboratory practicals are used to reinforce the relevant lectures. Revision lectures occur in the summer term.