2019/20 Undergraduate Module Catalogue

COMP2611 Artificial Intelligence

10 creditsClass Size: 335

Module manager: Dr Ali Gooya
Email: a.gooya@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2019/20

Pre-requisite qualifications

Either
COMP1421 Fundamental Mathematical Concepts
Or
ELEC1704 Further Engineering Mathematics

This module is not approved as a discovery module

Module summary

Artificial intelligence is a developed field within computer science and is rapidly evolving. The foundations of this field have roots in the work of Alan Turing investigating the boundary between human intelligence and computers. Technologies developed in the field of artificial intelligence have found their way into everyday life and form services and infrastructure that we rely on on a day to day basis. Such services and infrastructure include internet search, predictive text, speech recognition and automation.This module covers the foundations of the topics in artificial intelligence and considers its uses in a wide range of applications as well as the ethical and legal issues that arise.

Objectives

This module provides the foundations of artificial intelligence and considers the legal, ethical and social issues surrounding the use of artificial intelligence.

Learning outcomes
On successful completion of this module a student will have demonstrated the ability to:

- deconstruct the ethical arguments surrounding artificial intelligence and its applications.
- employ artificial intelligence techniques to solve real world problems.
- evaluate the effectiveness of artificial intelligence techniques when applied to real world problems.
- identify weaknesses and limitations of artificial intelligence techniques.

Syllabus

This module covers the following 3 topic areas:

- Artificial intelligence techniques : search techniques, logic, knowledge representation, probability, Markov models, Bayesian networks and genetic algorithms.
- Ethical issues : soft artificial intelligence, hard artificial intelligence, general artificial intelligence and singularity.
- Applications of artificial intelligence : text mining, game play and searching, object recognition.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	22	1.00	22.00
Practical	9	2.00	18.00
Private study hours			60.00
Total Contact hours			40.00
Total hours (100hr per 10 credits)			100.00

Opportunities for Formative Feedback

Coursework and labs.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Practical	Lab Implementation	10.00
Report	Project Report	10.00
Total percentage (Assessment Coursework)		20.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams

Exam type	Exam duration	% of formal assessment
Standard exam (closed essays, MCQs etc)	2 hr 00 mins	80.00
Total percentage (Assessment Exams)		80.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 30/04/2019

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