This module addresses:

Theory & Knowledge Exchange
Overview of AI paradigm
Philosophical foundations of AI
Knowledge representation
Inference
Expert systems
Classical and modern approaches to AI
The main techniques that have been used in AI, and their range of applicability
Challenges for the future of AI

Technology & Resources
Data mining

ractical Content
Problem solving and search Data Mining
Data Acquisition
Data pre-processing
Data Segmentation
Data Transformation (Feature Extraction and Feature Selection)
Data cleaning and data labelling

REPORT: A review of AI history and key philosophical issues that underlie AI for the given task scenario (e.g., Digital Health monitoring, Crowd and traffic Management, or Smart Homes) (Learning Outcomes 1 and 2)

PRACTICAL DEMONSTRATION: A practical demonstration of a design, implementation and testing of an AI software solution. Students will be expected to analyse a given task scenario to define the business problem and they will need to design, develop, and test their AI solution using the theories and practices covered in the indicative content (Learning Outcomes 3 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 a critical understanding of the history of artificial intelligence (AI) and its foundations. Knowledge and Understanding, Learning

2. Demonstrate a critical understanding of key philosophical issues that underlie AI.
Knowledge and Understanding, Learning, Analysis, Reflection

3. Apply basic principles of AI in solutions that require problem solving, inference,perception, knowledge representation, and learning.
Analysis, Reflection, Problem Solving

4. Demonstrate proficiency developing applications in an 'AI language', expert system
shell, or data mining tool.
Problem Solving, Reflection, Communication, Application

JetBrains PyCharm (IDE for Python)
Scikit-learn API, or similar API
Datasets from Kaggle, Weka, MIMIC, or similar sources
RapidMiner

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:
Raschka, S. (2017) Python machine learning: machine learning and deep learning with Python, scikit-learn, and TensorFlow. EAN: 9781787126022
Campbell, C, (2020), PYTHON PROGRAMMING: 3 BOOKS IN 1: The Complete guide to Learn Everything you Need to Know about Python, ISBN: 180154767X
Rothman, D, (2020), Artificial Intelligence by Example: Acquire advanced AI, machine learning, and deep learning design skills, 2nd Edition, Packt Publishing; 2nd edition, ISBN-10: 1839211539

Optional Text/Resource:
Wongchoosuk, C. (2018) Intelligent System. IntechOpen.
Boden, Margaret A. (1996) Artificial Intelligence. ISBN: 0080527590;9780080527598
Engelbrecht, A.P. (2007) Computational intelligence: an introduction. 2nd edn. Hoboken, N.J: John Wiley. ISBN: 0470017333

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

Artificial Intelligence is the automation of activities we normally attribute to human thinking and rationality, such as problem-solving, decision-making, and learning. AI lives within the intersection of many classic disciplines, including philosophy, neuroscience, behavioural economics, computer science, and mechanical engineering. This module introduces students to the basic principles, and techniques of AI. Emphasis will be placed on the teaching of those fundamentals, and an assigned project to promote a ‘hands-on’ approach for understanding, as well as a challenging avenue for exploration and creativity.