Computer Science with Data Analytics MSc
2 Years | Distance Learning | Upcoming Intakes: January 2025, April 2025

This module is design to develop your understanding of the conceptual basis for current database technology of which you will subsequently be able to apply such knowledge in implementing database applications.

Specifically you will be able to understand how to analyse, model, design, develop and manipulate databases. Furthermore, you will appreciate limitations of existing data models and the need for database programming to achieve complete solutions, write transactions and procedures for data manipulation, specify security for operations, and apply business rules.

You will also gain knowledge of alternative data models, their rationale, advantages and disadvantages, construct alternative data representations for contemporary data processing application. Moreover, you will get an appreciation of non-traditional data types, systems and applications (e.g., NoSQL Databases). You will learn how to use data for business reporting, exploratory data analysis and advanced data analytics. In addition, you will realise the responsibilities of database designers with respect to professional, legal, security and ethical issues.

Through the completion of this module you will learn the requirements for developing secure web applications to industry standards, including the technical and architectural components of the web, considering accessibility issues. You will also learn how to apply the tools and techniques required for secure web development and develop practical skills to build a web application that interacts with a database. Issues associated with the deployment of a web application will also be discussed, including how to audit and correct security deficiencies by following leading industrial practice.

The syllabus of the module will include:
• The technical and architectural components of the web
• HTML and CSS and their application to building a web site
• Client and Server programming to deploy a secure web application that interacts with a database• Security issues in the deployment of a web application that is both usable and accessible

The aim of the module is to provide you with the knowledge and practical skills for applying modern analytical techniques to business data. The module combines both theoretical and practical approaches so that you will have the skills to tackle problems in various realistic business settings.

Indeed, this module is primarily concerned with examining and analysing (big) data arising from business(es) and to relate the extracted information to strategic, tactical and operational decision-making in organisations. You will cover topics such as:

• Data processing and big data
• Exploratory data analysis
• Probability and distributions
• Hypothesis testing
• Correlation and regression analysis
• Classification
• Distance measures
• Clustering

This module is designed to develop your knowledge; understanding and skills in object oriented programming and program design concepts, using an object first approach. Specifically, you will learn how to design, implement, test and document programs and will gain practical programming experience by solving small scale problems. In addition, you will cover the need for standards and the principles of quality. In particular, the syllabus of the module will cover topics such as:

• Programming: simple data types and calculations; classes, objects, inheritance, interfaces, polymorphism; methods, constructors; parameter passing; arrays and strings; simple collection classes; statements for selection and iteration; exception handling; file and stream handling; APIs
• GUI programming : event driven programming, GUI components
• Tools: use of a compiler and associated Integrated Development Environment (IDE). Documentation tools.
• Program testing: purpose of testing, black box and white box testing. Use of tool support.

Since the module is intended for graduates from disciplines other than Computing, no previous programming experience is assumed.

In this online module you will learn various digital technologies that will work with AI for various real-world applications, and investigate how these technologies can transform the business, finance, manufacturing, etc. Specifically the module will cover the following key topics, including:

• Digital transformation technology
• Artificial intelligence
• Machine learning
• Big data
• Internet of Things (IoT)
• Blockchain
• Robotics
• Clouds
• Cyber security and privacy
• Industry 4.0

The aim of this module is for you to undertake a substantial academic research project at Masters level, produce a dissertation based on this work and present your findings. Your project itself will comprise a major piece of independent and original research centred at the forefront of your programme discipline. This takes place within the wider sphere of Computer Science.

In order to develop the necessary research knowledge and capabilities to successful complete the study, the module will begin with a taught stage where you develop a solid understanding of research methodology and methods alongside wider project management and academic skills required to successfully complete a research project. You will then progress to the completion of your project which will require you to develop, consolidate, and apply your independent research, academic study, and research skills to the investigation of a topic of your own choice that is relevant to your programme of study. You will experience the full life cycle of a research project from initial conception, development of a research proposal, critical review of the literature, planning and design of the research study to the implementation of your research, analysis of the findings, evaluation, reflection and dissemination.

You will present your work in a written report and recorded oral presentation.

Throughout this module you will develop knowledge and skills that will enable you to tackle a realistic big data problem, using some of the principal machine learning techniques and statistical approaches used in big data analysis. Furthermore, you will learn how to implement your solution using an industry leading Cloud computing provider together with appropriate distributed processing environments.

You will learn how to host multi-terabyte sized big datasets using a cloud service provider. This will includes provisioning a commercial cloud provider, and then mastering appropriate distributed operating systems, such as Hadoop. You will also learn approaches to processing and analysing big data, based on advanced statistical processing, supervised and unsupervised machine learning algorithms and other state of the art big data analytic methods. Such techniques include clustering algorithms, pattern based information extraction, linear and non-linear regression, and feature based models. Inevitably, much work on big data analysis is statistical, so you will therefore develop some relevant statistical understanding. As data visualization is frequently critical in helping to develop hypotheses about the data, you will also cover and apply problem relevant 2D and 3D visualization methods where appropriate to the particular datasets.