2020/21 Undergraduate Module Catalogue
COMP2611 Artificial Intelligence
10 creditsClass Size: 350
Module manager: Dr Ali Gooya
Email: a.gooya@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2020/21
Pre-requisite qualifications
EitherCOMP1421 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 |
| In-course Assessment | Coursework | 10.00 |
| In-course Assessment | Online Test 1 | 30.00 |
| In-course Assessment | Online Test 2 | 30.00 |
| In-course Assessment | Final Assessment | 30.00 |
| Total percentage (Assessment Coursework) | 100.00 | |
Exercises sheets will be provided for students. Sample solutions will be made available via tutorial classes or on Minerva. This module will be reassessed by an online time-constrained assessment.
Reading list
The reading list is available from the Library websiteLast updated: 29/01/2021 15:43:24
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