Computer Science and Artificial Intelligence

FACULTIES

Computer Science and Artificial Intelligence

Engage deeply with core areas of computer science, such as programming, data analysis, and machine learning, gaining both technical knowledge and an understanding of the ethical and societal impacts of AI.

The programme covers foundational modules like computer science, programming, artificial intelligence, and machine learning, with a strong emphasis on both theoretical knowledge and practical skills. Students will learn through hands-on projects, be taught programming languages, and software development techniques. Our curriculum also highlights ethical considerations and societal impacts of AI, encouraging a responsible approach to technology.

Core objectives

The course aims to nurture critical thinkers, creative problem solvers, and responsible technology users. By the end of the programme, students will possess a well-rounded skill set and a clearer sense of possible specialisations and career paths within the technology sector

Fundamental Engineering Principles

Provide students with a solid grasp of core computer science principles and the foundational theories of artificial intelligence.

Practical Skills Development

Develop skills in programming languages, software development, and the use of AI tools and frameworks through hands-on projects and exercises. 

Critical Thinking and Problem-Solving

Enhance analytical skills and the ability to approach complex problems methodically and creatively. 

Ethical and Societal Implications

Foster an awareness of the ethical considerations and societal impacts of AI technologies, encouraging responsible and informed application of AI. 

Innovation and Research

Inspire students to explore cutting-edge technologies, innovate solutions, and engage in research to contribute to the advancement of the field. 

Core modules

Introduction to Computer Science

This foundational module introduces students to the key principles of computer science, covering topics such as binary systems, hardware components, computational logic, and the structure of computer systems. The module provides a historical overview of computing, explaining how early innovations have evolved into today’s technology landscape.

Programming Essentials

This module introduces students to programming concepts through Python. Students learn about variables, loops, conditionals, and functions as they begin to code simple applications, emphasising problem-solving and debugging techniques. This module also touches on algorithmic thinking, giving students tools to plan and write efficient code.

Foundations of Artificial Intelligence

This module provides an introductory overview of artificial intelligence, including its historical development, fundamental concepts, and current applications. Students learn about machine learning, neural networks, and natural language processing, discussing how AI is applied in fields such as healthcare, finance, and entertainment. Ethical considerations, including privacy, bias, and accountability in AI, are discussed to help students develop a thoughtful approach to AI.

Machine Learning Techniques

This module introduces students to core machine learning techniques, and guides them through the process of training models on datasets. Students learn to differentiate between types of machine learning and to select appropriate algorithms for various tasks. Handson activities focus on applying simple machine learning models, allowing students to experience the iterative nature of model training and tuning.

Data Science and Analytics

This module focuses on the data science workflow, teaching students the steps from data collection to analysis and visualisation. Students learn to identify meaningful trends in data and present their findings in a clear and impactful way. This hands-on approach equips students with valuable skills in data analysis, a foundation for more advanced work in AI and analytics.

Robotics and Automation

This module introduces students to robotics principles, covering topics like sensors, control mechanisms, and simple automation tasks. Students work with basic robots, programming them to perform tasks such as navigating a course or picking up objects. The module emphasises the connection between mechanical and electronic components, showing how robots use sensors to interact with their environment.

Ethics in AI

This module explores the ethical and societal implications of AI, examining topics such as data privacy, algorithmic bias, and AI’s impact on employment and social equity. Through discussions, case studies, and debates, students consider both the potential benefits and risks of AI technology. By developing these skills, students become informed participants in conversations about the future of AI and its role in society.

Cybersecurity Fundamentals

This module covers cybersecurity basics, such as data protection, cryptography, and the identification of security threats. Students learn how data encryption protects information and how security protocols defend against common attacks. Hands-on labs allow students to experiment with security tools, teaching them best practices for digital safety. This module provides an essential foundation for understanding digital security and managing risks in an increasingly interconnected world.

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