Teaching and assessment for Artificial Intelligence MSc

A person wearing over ear headphones, working at a computer in an I.T suite.

Teaching

You will take part in highly interactive teaching sessions. This is where you will apply what you learn in a practical, hands-on environment. These sessions will include:

Lectures
- You will explore key concepts, theories, and cutting-edge AI developments
Workshops
- You will engage in hands-on programming, AI model development, and problem-solving activities.
Tutorials
- This is where you will get personalised guidance and feedback to support your learning
Industry Sessions
- You will learn directly from AI and software development professionals. They will teach you about how the skills you acquire can be applied in real-world scenarios

Assessment

You will be assessed through a combination of coursework and end-of-semester exams.

Coursework is highly practical. It is designed to develop the skills you need in industry. Assessments may include:

developing AI models and algorithms
programming and software engineering tasks
writing reports on AI ethics and system design
building web applications and AI-powered tools
testing and optimising software solutions
analysing real-world AI challenges and proposing solutions
presenting technical concepts to industry experts

Modules

Core Modules

These modules are an essential part of your course.

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Module code: AC51048 Credits: 20 Semester: Semester 2

This module explores the principles and technologies behind big data and large-scale data processing. You will learn how to manage, analyse, and extract insights from massive datasets using distributed computing frameworks and programming tools.

Big Data Analysis and Distributed Programming full module details

Module code: CS51004 Credits: 10 Semester: Semester 1

Look into the ethical, societal, and regulatory dimensions of artificial intelligence. You will examine how AI systems impact privacy, fairness, and accountability, and how governance frameworks shape their development and use.

Societal Impact and Ethics of Artificial Intelligence full module details

Module code: CS51006 Credits: 20 Semester: Semester 1

Introduces the fundamental concepts and techniques of computer vision and image processing. You will explore algorithms for classification, segmentation, object detection, motion analysis, and 3D vision, while gaining hands-on experience with deep learning models for visual AI.

Computer Vision and Image Processing full module details

Module code: CS51009 Credits: 20 Semester: Semester 1

Learn how computers detect patterns and make predictions with machine learning. Explore supervised techniques like linear models, logistic regression, and neural networks, while gaining hands-on experience with modern tools.

Machine Learning full module details

Module code: CS52003 Credits: 20 Semester: Semester 2

Learn Natural Language Processing (NLP), from foundational models to modern transformers. Develop and fine-tune NLP systems for tasks like classification and summarisation, while considering ethical and societal implications.

Natural Language Processing and Large Language Models full module details

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