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Studying Artificial Intelligence and Data Science at È«Ãñ²ÊƱ enables graduates from Psychology and related fields to augment their skills with avantgarde techniques from Artificial Intelligence, Machine Learning, Cognitive Psychology and Neuroscience.

Heavily influenced by research from both disciplines, this programme will allow you to exploit both disciplines to advance in your chosen career path.

We retain a strong sense of professionalism and ethics throughout the programme, highlighting the sensitive nature of the subject matter.

What will you study on this course?

Academic Year 1
Code	Module	Credit	Level	Module Coordinator
ICE-4001	MSc Individual Project 2024-25	60	Level 7	Core
Academic Year 1 Semester 1 Modules
Code	Module	Credit	Level	Module Coordinator
ICE-4006	Data Science 2024-25	20	Level 7	Compulsory
ICE-4101	Introduction to Programming 2024-25	20	Level 7	Compulsory
ICE-4211	Principles of Machine Learning 2024-25	20	Level 7	Compulsory
Academic Year 1 Semester 2 Modules
Code	Module	Credit	Level	Module Coordinator
ICE-4003	Advanced Research Methods 2024-25	20	Level 7	Core
ICE-4732	AI & Game Design 2024-25	20	Level 7	Compulsory
ICE-4721	Natural Language Processing 2024-25	20	Level 7	Compulsory

Module Overview

ICE-4001, MSc Individual Project - This is an amazing opportunity to undertake a large individual project which brings together all of the theory and skill that you have developed during the taught part of the course. You will select from a range of themes and then work with you project supervisor to develop you aims and objectives. The topics are aligned with the school’s research interests along with other applied areas.

ICE-4006, Data Science - Data Science provides students the skills and knowledge to a data-driven questions that interests them. This helps build the intuition all Data Scientists need for applying appropriate techniques and algorithms to problems.

ICE-4101, Introduction to Programming - This module provides an introduction to the fundamental concepts and techniques of programming. It will involve learning how to write computer programs through weekly exercises and computing laboratories. The student will gain the know-how about how to develop non-trivial programs using advanced programming concepts, specifically in the Python programming language, a language that is now becoming one of the important programming languages in Computer Science and Data Science. The module will be assessed by 100% computer laboratory course work.

ICE-4211, Principles of Machine Learning - Machine learning lies at the crossroads of statistics and computer science, permeating diverse sectors including science, high-tech, retail, finance, transportation, and more. At its core, machine learning strives to craft data-powered models for comprehending and foreseeing real-world system behaviours, fuelling the heightened demand for machine learning expertise.

ICE-4003, Advanced Research Methods - This module provides research skills with a focus on the Research Project but in a wider context.

ICE-4732, AI & Game Design - AI has a wide variety of uses in video games and other real-time applications, including controlling character motion and behaviour, animation systems, navigation and search, directing gameplay, learning and evolution, and procedural generation. AI & Game Design looks at these modern real-time AI techniques through the lens of video game development.

The module will teach the theory and application of modern AI techniques and tools. You will also put this theory into practice by developing a video game that showcases AI, using a modern game engine like Unity or Unreal.

In the semester-wide assignment, you will be given freedom to design any kind of video game you like that showcases AI techniques. You will also write a blog that documents your game's development. Theoretical aspects of AI in game design and development will also be assessed in an end of semester exam.

ICE-4721, Natural Language Processing - In this module you will learn a vast array of new skill and toolsets, you do natural language processing in Python using the NLTK and text processing methods using Unix tools such as sed, awk. You will explore topics such as Computational Linguistics and Natural Language Processing: Zipf’s Law; Heap’s Law; the sparse data problem; the zero frequency problem; regular expressions; n-grams; language modelling; NLP pipeline and in Information Retrieval.

A recognised undergraduate degree at 3rd class minimum, or international equivalent is required.