This module will enable students to gain a deeper understanding of key concepts in artificial intelligence. It covers the foundations of artificial intelligence, the historical evolution of AI, fundamental principles, problem-solving methodologies, knowledge, and reasoning, and addresses uncertain knowledge and reasoning. The curriculum extends to various types of learning, including practical natural language processing, and delves into agents' capabilities in communication, perception, and action. The module also encompasses artificial intelligence, machine learning, and deep learning algorithms, enabling students to grasp techniques applicable to real-life problem-solving. With a focus on real-life problem-solving, ethical considerations, and the integration of AI with smart technologies, this module equips students with a well-rounded perspective on the diverse facets of artificial intelligence.

A 1.5-hour examination weighted at 30% assessing learning outcome 2. Meeting AHEP 4 Outcomes: M2, M5

A 3000-word individual report weighted at 70% assessing learning outcomes 1, 2, 3, and 4. Meeting AHEP 4 Outcomes: M1, M2, M5 and M17

Professional Body requirements mean that a minimum overall score of 50% is required to pass a module, with each element of assessment requiring a minimum mark of 40% unless otherwise stated.

This module will enable students to gain understanding, apply knowledge, analyse and evaluate problems and create solutions through a variety of activities, including:

- Learning on all aspects of the indicative content will be facilitated by classroom-based lectures, tutorials, laboratory-based practical experiments.

- Independent study: reading, information gathering, presentations, student-centred learning, assignment preparation.

1. Demonstrate a deep systematic understanding and critical evaluation of the application of Artificial intelligence and Machine learning. (AHEPs 4: M1)

Enquiry,

Knowledge and Understanding, Learning

2. Analyse complex real-life problems and apply appropriate analytical approaches, and experimental, and simulation techniques to solve these problems using Artificial Intelligence tools. (AHEPs 4: M2, M5)

Analysis,

Knowledge and Understanding, Application

3. Critically evaluate and compare the potential solutions to the explored complex problems. (AHEPs 4: M2, M5)

Problem Solving,

Reflection

4. Demonstrate expertise in planning, designing, developing, and presenting optimised resources for a practical scenario where artificial intelligence can be applied. (AHEPs 4: M1, M5, M17)

Application,

Communication

PCs running with software such as Python, MATLAB and LabVIEW.

Alpaydin, E. (2020), Introduction to machine learning. MIT press. ISBN-13: 978-0262043793

Brady M., et al., (2012), Robotics and Artificial Intelligence, Springer Berlin Heidelberg. ISBN-13: 978-3642821554

Goodfellow, I. et al., (2017), Deep Learning (Adaptive Computation and Machine Learning Series). MIT Press, Cambridge, Massachusetts. ISBN-13: 978-0262035613

Hopgood, A. A., (2021), Intelligent systems for engineers and scientists: a practical guide to artificial intelligence. CRC press. ISBN-13: 978-0367336165

Shalev-Shwartz, S. et al., (2014), Understanding Machine Learning: From Theory to Algorithms, Cambridge University Press, Cambridge, England. ISBN-13: 978-1107057135

Stuart, J. et al., (2020), Artificial Intelligence: A Modern Approach, Prentice Hall, New Jersey, 4th edition. ISBN-13: 978-0134610993

Tom M., et al., (2013), Machine Learning, McGraw Hill Education; New York. ISBN-13: 978-1259096952

This module equips you with essential skills to thrive in the rapidly evolving field of Artificial Intelligence (AI). It enhances your employability across various industrial and academic AI-related roles by focusing on modern statistical machine-learning methods, core AI principles, contemporary AI and machine-learning techniques, and their real-world applications. You will develop the ability to evaluate implementations, handle practical data and scenarios, and adapt techniques to real-world AI challenges, making you well-prepared for success in this dynamic field.