This module addresses the following topics:

Theory & Knowledge Exchange
Understanding various applications of AI application
Goals in AI Agents and Robots
Ubiquitous applications
Introduction to Legal, Social, Ethical and Professional Issues
Artificial Intelligence and Smart technologies

Technology & Resources

Technological Infrastructure / Networking for AI applications

Practical Content
Expert Systems
Computer Vision
Natural Language Processing

REPORT:

A detailed review of AI applications, their productiveness and effectiveness, and the current limitations and societal implications for a given task scenario (e.g., Digital Health monitoring, Crowd and traffic Management, and Smart Homes etc.). (Learning Outcomes 1 to 4).

PRESENTATION:

A presentation of 10 minutes, plus 5 minute Q&A if required, discussing a selected scenario and how AI has enhanced productivity and effectiveness of the sector for the given task scenario. The presentation should include works that are current for these types of AI application (including examples, technologies, research, and case studies) and a reflection on the scope of the AI used within the given task scenario. (Learning Outcomes 1, 2 and 4).

All teaching sessions will blend theory and practical learning. Students will be introduced to curriculum concepts and ideas and will then be able to apply theory to practical examples within the same sessions. In addition, students will be provided with a range of resources for independent study such as case studies, academic papers and industry stories. There will be a mixture of practical and theoretical formative (mock or practice) exercises which will help students build knowledge and confidence in preparation for summative (formal) assessment.

1. Demonstrate awareness and a fundamental understanding of various applications of AI, as well as its benefits to enhance productivity and effectiveness in its use.

Knowledge and Understanding, Learning

2. Demonstrate a critical understanding and analysis of technologies and data science in an AI application.

Knowledge and Understanding, Learning, Analysis

3. Show understanding of the specifics and the intricacies of AI methodologies.

Problem Solving, Reflection, Communication

4. Demonstrate an ability to share in discussions of AI, its current scope, and limitations,and societal implications.

Knowledge and Understanding, Problem Solving, Reflection, Communication

Library resources (books, journals accessible online, full IEEE Xplore access to academic papers, and various magazines)

All texts and electronic resources will be updated and refreshed on an annual basis and available for students via the online Study Links resource platform. All reference materials will be collated and curated and aligned to Equality, Diversity & Inclusion indicators.

Core Text/Resource:

Arankalle, C, Dwyer, G and Geerdink, B et. al (2020), The Artificial Intelligence Infrastructure Workshop: Build your own highly scalable and robust data storage systems that can support a variety of cutting-edge AI applications, Packt Publishing, ISBN-10:1800209843

Ponteves, H, (2019), AI Crash Course: A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python, Packt Publishing, ISBN-10:1838645357
Riccoboni, A, (2020), THE A.I. AGE, Critical Future, ISBN-10: 1513657291

Optional Text/Resource:

Stuart J., et al., (2009), Artificial Intelligence: A Modern Approach, Prentice Hall, New Jersey, 3rd edition.
Tom M., et al., (2017), Machine Learning, McGraw Hill Education; New York.
Goodfellow I., et al., (2017), Deep Learning (Adaptive Computation and Machine Learning Series). MIT Press, Cambridge, Massachusetts.
Shalev-Shwartz S., et al., (2014), Understanding Machine Learning: From Theory to Algorithms, Cambridge University Press, Cambridge, England.

Advanced/Supplementary Text/Resource:

Bramer, M.A. (2016) Principles of data mining. 3rd edn. London: Springer, ISBN:1447173066 9781447173069 Engelbrecht, A.P. (2007) Computational intelligence: an introduction. 2nd edn. Hoboken, N.J: John Wiley. ISBN: 0470017333 Brady M., et al., (2012), Robotics and Artificial Intelligence, Springer Berlin Heidelberg, ISBN-10: 0262523922

All resources will be updated regularly and available via a module KeyLinks online function.

This module will allow students to research various applications of AI application and benefits of Artificial intelligence to enhance productivity and effectiveness of given business / application sectors. Using this research, students will present their findings. The module will also introduce students to the world of AI and several concepts and terminologies that can be used to implement AI applications.