This module provides a foundational understanding of Artificial Intelligence, designed for undergraduate students in the BEng AI programme. It aims to introduce key concepts, techniques, and applications of AI, fostering a solid grounding for further study in the field. By integrating theoretical knowledge with practical skills, this module prepares students to engage with more advanced AI topics and real-world challenges.
A Demonstrate an introductory understanding of fundamental AI concepts, including intelligent agents and the basic principles of AI and machine learning. B Utilize basic AI techniques and algorithms to explore AI-related problems, demonstrating familiarity with tools used to model AI problem-solving processes. C Analyse the performance and limitations of simple AI systems and algorithms.
The teaching philosophy of the module follows very much the philosophy of Syntegrative Education. This philosophy is carried through in terms of assessment, with reduction on the use of exams and increase in coursework, especially problem-based assessments that are project focused. This module will be mainly delivered by lectures with case studies, including practical sessions in Computer labs and reflection sessions. The lectures cover the content outlined in the syllabus, introducing fundamental AI topics. Labs are designed to equip students with essential programming and hands on skills in module-related areas. Through individual project, students gain practical experience in implementing and experimenting with AI and undertaking independent study and research on industry focused real-world problems. Case studies will be used to provide students with real-world examples of how the concepts and techniques covered in this module can be applied. Lab/Practical sessions will allow students to apply the techniques, data analytics tools to solve real-world industry focused problems and conduct market and industry analysis. This module will leverage generative AI to enhance course content and teaching methods in line with the learning outcomes. By integrating advanced AI technologies, we aim to improve the efficiency of teaching and interaction, while fostering greater student autonomy and flexibility in learning