IS41100 Artificial Intelligence

Academic Year 2021/2022

Artificial Intelligence systems are becoming increasingly influential in society. The purpose of this module is to equip students with a comprehensive understanding of AI without the requirement of a technical background. The goal of the module is that students will be able to critically engage with the development and evaluation of AI systems from a multi-disciplinary perspective. The history of AI is examined along with its philosophical foundations and implications in terms of society and ethics. The course presents an overview of different branches of AI and contemporary debates in relation to approaches to AI. From this module students will gain a solid understanding of the foundations of AI, how it has evolved over time and current trends and debates in AI development.

This module also provides an introduction to AI's most popular programming language - Python. No prior knowledge of programming is assumed, but students will learn how to write Python code and will gain an introduction to common AI applications.

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Curricular information is subject to change

Learning Outcomes:

On successful completion of this module students should be able to:

1. Demonstrate an overall understanding of AI and its approaches
2. Critically evaluate different approaches to the development of AI and their implications from a societal perspective.
3. Use an AI technology in a research project
4. Engage in contemporary debates in the field of AI
5. Critically evaluate and assess the development of AI systems
6. Write python code and run a machine learning algorithm

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Computer Aided Lab

12

Autonomous Student Learning

165

Total

201

Approaches to Teaching and Learning:
This module includes lectures, labs, reflective learning, critical reading, class activities, debates and project work.



 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: - Critical evaluation of an AI system
- Project that uses an AI technique to address an issue with Python
Unspecified n/a Graded No

50

Multiple Choice Questionnaire: A timed online quiz in Brightspace will access the fundamentals of Artificial Intelligence Unspecified n/a Alternative linear conversion grade scale 40% No

10

Assignment: Critical evaluation of contemporary AI journal article Unspecified n/a Graded No

20

Assignment: Essay or report paper critically assessing a topic within the foundations of AI Unspecified n/a Graded No

20


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Online automated feedback

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Thompson Kwarkye Lecturer / Co-Lecturer
Dr Arjumand Younus Lecturer / Co-Lecturer