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Learn how to build technologies that use human-like intelligence to create and innovate
Aberystwyth University’s 100% online MSc Artificial Intelligence equips you with the fundamental knowledge and technical expertise to develop AI-driven solutions that support business growth. The programme explores key areas such as decision-making, predictive modelling, speech recognition, image processing, and human-AI interaction, equipping you to design and implement intelligent systems that align with business objectives.
You will explore the role of data and algorithms in AI applications across various industries, including healthcare, automotive, manufacturing, information technology, and eCommerce. Through real-world case studies, you will refine your problem-solving skills and gain practical experience in applying AI and ML strategies to industry-specific challenges.
Purpose-built to fit around professional and personal commitments, this programme prepares you for advanced roles in AI and machine learning, enabling you to navigate the rapidly evolving technology landscape and drive innovation across multiple sectors.
What will you study?
Build a strong foundation in computer science and AI, mastering practical techniques to solve real-world problems. You’ll enhance analytical and problem-solving skills, collaborate across disciplines to develop innovative AI solutions, and prepare for leadership roles in this evolving field, positioning yourself for success in AI-driven industries and research.
Key knowledge and skills taught on this course:
Learn AI and computer science fundamentals
Apply AI techniques to solve real-world challenges
Develop analytical skills for AI-driven innovation
Collaborate to create interdisciplinary AI solutions
Prepare for leadership roles in AI industries
Admission requirements
Entry requirements
To study Aberystwyth’s 100% online MSc Computer Science with Artificial Intelligence and Machine Learning you will need to have completed:
A recognised undergraduate or postgraduate degree (or equivalent qualification) from an accredited college, institution, or university, equivalent to or higher than a UK bachelor’s degree with honours.
OR
2 years’ minimum relevant work experience
English language requirements
Applicants whose first language is not English, or who haven’t recently studied or undertaken work experience in English, will need to demonstrate proficiency by completing an approved English language test such as IELTS (6.0 overall with no individual sub-scores under 5.5), or equivalent.
Modules
Principles of Programming Languages
Examine the origins and evolution of programming languages, studying how different languages like Java and Lisp implement abstractions, including data types and control structures. This module also covers advanced programming features such as exceptions and polymorphism, and the role these features play in creating robust, flexible applications. Additionally, you will explore various programming paradigms and their core concepts.
Operating Systems
Gain insight into the core aspects of operating system design and implementation. Topics include system concepts such as process and memory management, coordination, device drivers, and file systems. You will examine how different operating system types - batch, multitask, distributed, and mobile - affect coding decisions and how their design influences system functionality. Case studies will help you understand the real-world applications of various operating systems and their impact on software development.
Algorithms & Data Structures
Learn how to analyse and design computer algorithms and data structures. The focus is on evaluating algorithm efficiency and implementing data objects, programming styles, and performance expectations. Key topics include understanding algorithmic design patterns, such as data concepts, arrays, stacks, queues, trees, and graphs. You will explore how these concepts contribute to effective programming and problem-solving in coding design. Additionally, you’ll study methods for optimising software performance to ensure solutions are scalable and reusable for growth.
Computer Architecture
Explore how to evaluate technological solutions and select the appropriate computer architecture to support organisational needs. By understanding both hardware and software components, you’ll learn how to design solutions that meet usability and performance requirements. You will also study how to make architecture decisions for successful implementations, focusing on building systems that integrate seamlessly with organisational objectives.
Data Warehousing and Data Mining
Explore the fundamentals of data warehousing and data mining, focusing on techniques like big data analysis, prediction, classification, and clustering. You will understand how data mining integrates with databases to uncover patterns and insights. By working with tools and techniques for querying and manipulating databases, you’ll learn how to apply these methods to real-world business applications and decision-making.
Machine Learning
Learn the fundamentals of machine learning, exploring key algorithms and how they apply to real-world data. The module covers essential techniques like regression, classification, neural networks, and deep learning. You will gain practical experience structuring data into models and using machine learning tools to solve business challenges, with a focus on creating systems that can learn from data and make informed predictions.
Artificial Intelligence & Machine Learning
Explore the fundamentals of artificial intelligence and machine learning, learning how these technologies are transforming everyday lives and businesses. Topics include speech and face recognition, autonomous driving, and automatic scheduling. You will gain an understanding of the mathematical tools behind AI applications and examine how machine learning algorithms can be applied to solve real-world problems. Ethical considerations surrounding AI will also be discussed, helping you navigate its potential impact on society.
Computer Vision
Gain an introduction to computer vision as it applies to building artificial intelligence systems that process visual data through deep learning algorithms like neural networks. Topics include image formation, camera processing, and the extraction of features such as stereo images, filtering, edge detection, and object recognition. By exploring real-world applications in fields like gaming, self-driving cars, and medical imaging, you will understand how visual data can be used to make intelligent decisions and improve user experiences.
Natural Language Processing
Explore modern natural language processing (NLP) techniques, including speech recognition, sentiment analysis, and machine translation. You will learn how statistical methods and deep learning are used to analyse and generate human language. The module covers the application of NLP in machine learning and its integration with tools like classification models, neural networks, and transfer learning. You will also develop an understanding of how NLP can be applied to business problems, such as chatbots and customer support systems.
Network Security
Study key security concepts in computer and mobile networks, exploring issues such as LAN and WAN security, encryption, authentication, and risk mitigation. You will examine the infrastructure designs and security flaws that can impact networks and learn how to assess and strengthen network security. With a focus on troubleshooting and implementing security protocols, you will develop a deep understanding of how to protect and maintain network systems.
Research Project
Engage in an independent research project, applying the skills and knowledge gained throughout your studies. This module provides the opportunity to explore a specific area of interest in depth, allowing you to demonstrate your ability to design, analyse, and implement a solution to a real-world problem.
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