MSc Computer Science with Artificial Intelligence and Machine Learning

Programme Overview

This module is designed for students to develop a comprehensive understanding of research in computer science. The module examines the concepts and theories underlying research, as well as the practice of research. The module has an applied focus. The readings and assignments are designed to identify a feasible research topic and develop a research proposal for an academic project or dissertation. How research problems and questions may be identified, and the process of achieving thoughtful, effective and efficient research design are examined.

The importance of the literature review and how it can be carried out for optimal effectiveness in research are investigated. In addition, the module provides an overview of research methodologies and methods and the techniques of the research process. The philosophical and epistemological assumptions underpinning the research approaches and methodologies, as well as their role in determining the design and implementation of the research, are studied. Besides these aspects, the ethical aspects of research are also addressed. 

Programme Overview

This module is a continuation of Research Methods for Computer Science I in which the student will complete the project or dissertation presented in the first module. 

Programme Overview

You will learn how to analyse and design computer algorithms and data structures. The focus will be on methods for evaluating algorithm efficiency and implementation of various data objects, programming styles, and performance expectations. Course topics will include key areas required to understand algorithmic design patterns, such as data concepts, arrays, stacks, queues, trees, and graphs. You will apply these concepts to create effective programs and solve problems in coding design. In addition, you will learn the importance of enhancing the performance of a program to ensure it is optimised and reusable for overall growth.

Programme Overview

You will learn the fundamentals of artificial intelligence, usability, and how it is impacting everyday lives and businesses. Topics covered will include overviews of the concepts of AI usage such as speech recognition, face recognition, autonomous driving, automatic scheduling, machine learning, deep learning, and other areas. In addition, you will learn how mathematical tools are used to create applications and how you can use tools to solve AI problems in the real world. Finally, you will examine various AI ethical questions and concepts which impact people and businesses.  

Programme Overview

In this module, you will gain an introduction to computer vision when building artificial intelligent systems that process and perceive visual data through deep learning algorithms such as neural networks. Topics will include fundamentals of image formation and camera imaging processing including types of features such as stereo image, filtering, feature extraction, edge detection, alignment, object recognition, appearance, audio, language, and other functionality. You will research situations where imagery enhances artificial intelligence to capture the eye of the intended audience such as for gaming systems, self-driving cars, medical imaging, scientific applications, and other advancements in technology. As a result, you will understand how visual representations can be structured to make images more accurate depictions through computer vision tasks. 

Programme Overview

You will learn how to evaluate a new solution by determining the appropriate computer architectural design to implement for a software program. The core topics focus on understanding critical hardware and software functionality needed to ensure a solution can be designed that will meet the requirements for usability, performance, and support expectations of the program. In addition, you will learn strategies for making architectural decisions critical for successful implementations.

Programme Overview

You will study key security concepts, security issues and procedures in computer and mobile networks. Topics covered will include learning about the various types of security such as the security of LANs, WANs, databases, and network operating systems. You will analyse threats to computer networks by exploring designs of network infrastructure, potential security flaws, risk assessment and mitigation, and security concepts that impact various communication networks. You will develop knowledge to determine what network security capabilities are needed in architecture and how to apply them based on different situations. As a result, you will get a comprehensive understanding of when to use network intrusion detection and forensics technologies, cryptographic and authentication systems, access control mechanisms, internet routing and other protocols.

Programme Overview

You will learn the fundamentals of data warehousing and data mining. You will gain a deeper understanding of how data mining is used through hands-on experience in various areas such as big data analysis, prediction, classification, identification, clustering, and association. In addition, you will learn how data mining and databases work hand-in-hand from a user perspective in various data modelling, statistical analysis, designing schemas, querying databases, and manipulating databases. By the end of the course, you will understand key strategies on how to apply data mining technology to real-world applications, evaluate trends, and optimal design solutions.

Programme Overview

You will gain foundational knowledge on the importance of machine learning in artificial intelligence and explore modern algorithms in machine learning, focusing on practical applications to understand how to structure data into models that can be created and utilised. Throughout the course, there will be a core emphasis on how to understand the components needed when using data and information to develop such as software libraries, regression, classification, mixture models, neural networks, deep learning, ensemble methods and reinforcement learning. In addition, you will have knowledge of machine learning techniques and how they can be applied in various processes and real-world solutions. 

Programme Overview

In this module, you will learn about modern natural language process (NLP) and how it addresses differences in speech recognition and other patterns. You will explore statistical methods and deep learning concepts to understand syntactic and semantic analysis of text, sentiment analysis, question answering and translation. The goal is for you to understand how NLP works by using information available to provide adequate results back to the user in a business scenario. In addition, this course will cover how NTP fits in machine learning by discussing areas such as classifications, neural networks, model training and transfer learning. 

Programme Overview

You will examine the overall core aspects of operating systems design and implementation. Key topics include developing knowledge of operating systems by reviewing different types of OS to understand system concepts (process and memory management, process coordination, device drivers, file systems, starvation/deadlock), functionalities of files system management (such as log-structured file systems, distributed file systems, memory-based file systems), user interface, programs and implementation approaches and steps. In addition, you will utilise case studies to understand design approaches on how operating system types (batch, time-sharing/multitask, distributed, network, mobile, Microsoft windows, Apple iOS, Linux, etc.) may be used in a particular solution scenario and how they impact coding decisions.

Programme Overview

You will learn concepts of programming languages and design considerations to consider in implementing a solution. Key areas include learning about different types of programming languages, such as multiple programming paradigms, including functional and object-oriented programming like C++, Java, JavaScript, C#, and Python. You will gain foundational knowledge and concepts to incorporate the appropriate functionality, such as stack and heap, from a scalability and performance perspective when making software development design decisions for a solution. In addition, you will learn about software and application frameworks and various add-on components to ensure you are making a full design decision.