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Last modified: 25 May 2018 11:16

Course Overview

This course is aimed at people who want to learn the basics about the major problems that need to be solved to enable computers to be more useful companions in our daily lives, e.g. to get them to be able to understand our normal speech when we talk to them, or to be able to see and recognise the important objects in the world, or to be able to act as a helper in the home, like a robotic maid that could cook and clean.

Course Details

Study Type Undergraduate Level 1
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus None. Sustained Study No
  • Dr Frank Guerin

Qualification Prerequisites

  • Either Programme Level 1 or Programme Level 2

What courses & programmes must have been taken before this course?

  • Any Undergraduate Programme (Studied)

What other courses must be taken with this course?


What courses cannot be taken with this course?


Are there a limited number of places available?


Course Description

The first part of the course overviews important problems in Computing and AI (for example Natural Language Processing, Computer Vision, and Robotics), and a number of techniques which are used to tackle these problems (for example search, neural networks, and reinforcement learning). The second part of the course looks at relevant areas of Cognitive Science, including Psychology, Linguistics, Neuroscience and Philosophy. Finally the course looks at the history of Computing and AI and possible future scenarios.

Further Information & Notes

Assistive technologies may be required for any student who is unable to use a standard keyboard/mouse/computer monitor. Any students wishing to discuss this further should contact the School Disability Co-ordinator.

Degree Programmes for which this Course is Prescribed

  • BSc Computing Science
  • Bachelor Of Engineering In Engineering Electronic & Software
  • Computing Science Joint
  • Computing Science Minor
  • MA Computing
  • MA Information Systems and Management
  • MSci Computing Science w Ind'l Placement
  • MSci Computing with Industrial Placement
  • Master Of Engineering In Electronic & Software Engineering
  • Master of Engineering in Computing Science

Contact Teaching Time

46 hours

This is the total time spent in lectures, tutorials and other class teaching.

Teaching Breakdown


1st Attempt: 1 two-hour written examination (75%); Continuous assessment: a series of short tests (25%).
Resit: 1 two-hour written examination (75%); Continuous assessment mark carried forward (25%).

Formative Assessment

During lectures, the Personal Response System and/or other ways of student interaction will be used for formative assessment. Additionally, practical sessions will provide student with practice opportunities and short tests provide direct formative assessment.


Formative feedback for in-course assessments will be provided in electronically with incorrect answers highlighted and correct answers given. Additionally, formative feedback on performance will be provided informally during practical sessions.

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