From infrastructure and education to healthcare and climate change, data science is playing an increasingly important role in all aspects of the modern world.
There is a persistent and growing demand for graduates who have the practical skills and expertise to responsibly use data to combat some of the world’s greatest challenges and help businesses to thrive in a challenging global environment.
The 100% online MSc Computer Science with Data Science has been designed and developed by a team of experts to develop agile, flexible and dynamic graduates with the right blend of computer science and data science training and management skills to meet the demands of industry across a wide range of sectors.
The diverse skills acquired in this course will position you perfectly to take advantage of the skills shortages in data science careers across a broad spectrum of industries and sectors.
What makes the online MSc Computer Science with Data Science so innovative is that it is taught and studied entirely online, with no need to visit campus at any point. This achieves a key purpose of the course: to be universally accessible to learners based all over the world. The flexible course design ensures that all course content can be accessed on demand, at the times that suit you. This is key because it enables you to study around work and family commitments, continuing to earn without needing to put your career on hold or take a study break.
With six start dates a year, you’re not restricted to the traditional academic year and can begin your postgraduate study within weeks.
This master’s degree is taught in a carefully crafted online learning environment that incorporates innovative online teaching methodologies and is based on participation, interaction and collaboration.
Through discussion boards and forums, you will discuss course content with academics and fellow learners. You will participate in group tasks and have the opportunity to learn from and network with a diverse group of peers based all over the world.
Studying the online MSc Computer Science with Data Science, you will develop a critical understanding of the processes, techniques and methodologies of data science. You will develop the key skills needed to mine datasets and to extract meaning and insights through data analytics from complex real-world situations. You will also develop the communication, management and organisational skills needed to lead data science projects and to communicate findings to the wider organisation, including to non-technical audiences.
The highly skilled academic experts in the Department of Computer Science are research-active and many are engaged in cutting-edge projects – 85% of the research at The University of Wolverhampton was recognised as ‘world-leading’ or of ‘international importance’. Our computer science students have partnered with industry on high tech projects, examples of which include apps and software development for the NHS and the West Midlands police.
You should normally have, or be about to complete:
Or:
You will need to have access to a computer with administration access so that you can install the software to be used on the course.
If you are based in the UK, you may be eligible for a government postgraduate loan to cover the full costs of the course. You will need to self-fund your first module/s to enrol.
University of Wolverhampton alumni discount: If you have successfully completed an undergraduate degree at the University of Wolverhampton, you are eligible for a 10% tuition fees reduction.
This module is designed as an introduction to some of the central concepts and tools used in data science. As such it includes discussions on data capture, maintenance, processing, analysis and communication. You will examine a series of real-world case studies, and state-of-the-art software and algorithms will be used as tools within these case studies. You will explore: an introduction to data science; data capture; acquisition of data; data maintenance; data processing; data analysis; data communication; and intelligent decision-making. On completion of this module you will be able to extract meaning from data and communicate that meaning to non-specialist audiences, and you will be able to use software in the application of specialist algorithms and approaches to data processing and analysis.
This module looks at different data processing and mining techniques and state-of-the-art data processing and mining tools. The topics you will explore include an introduction to data mining and knowledge discovery process, data collection and processing with data types from a variety of sources, and social web mining. You will look at a variety of techniques and trends in data mining and will develop an understanding of: data models; the knowledge discovery process; data selection; pre-processing and cleaning; data mining algorithms and association rules; classification; clustering; text mining; social media mining; and data visualisation. After studying this module, you will be able to use all aspects of the knowledge discovery process from data collection and data processing to representation, applying cutting-edge data mining techniques to extract information from data. You will also develop your own data mining solution using a state-of-the-art data mining tool.
Data visualisation is an important visual method for effective communication and analysing large datasets. With the rapid increase of data volume and complexity, users often find it difficult to understand and make sense of the data. Through data visualisation, data is presented in a meaningful and interactive way to users, so that they can draw conclusions from data that sometimes are not immediately obvious, and hence manipulate and use the data for exploration, learning, communication, problem resolution and decision-making. The module will provide you with the knowledge of theoretical concepts of interactive data visualisation and presentation, creative design processes as well as the applications of interactive visualisation and presentation tools and techniques. You will explore: history of data visualisation; planning a visualisation; designing a narrative around data; how to create the right charts for your data; elements of poor design; perception; interactive data visualisations; use of software; and communication and telling a story with data. On completion of this module you will be able to understand and apply the fundamental concepts and techniques in data visualisation and use specialist software such as Tableau to produce visual insights into data and to present your findings to a non-specialist audience.
This is an introductory module in statistics and it assumes no prior knowledge of the subject. The module introduces the basics of descriptive statistics (including graphical methods), linear regression models and inferential statistics (including hypothesis testing). You will explore descriptive statistics, data types, measures of central tendency, measures of location, measures of dispersion, graphical methods, histograms, pie charts, stem and leaf plots, and box plots. You will also examine ordinary least squares regression and correlation, inference, estimation, hypothesis testing, and statistical software such as R and SPSS. Upon completion of this module, you will be able to solve problems concerning descriptive and inferential statistics, summarise data using suitable graphs and descriptive statistics, analyse the performance of statistical hypothesis tests, import data using an appropriate software tool and perform statistical analyses of the data.
The manipulation and management of data is fundamental to being a successful data scientist. This module equips you with the skills necessary to design and implement appropriate database systems to support the manipulation of data and keep it secure. The module will also develop an understanding of the different types of database systems to ensure an appreciation of where they are applicable. On this module, you will study: an introduction to database concepts and techniques; database design (Oracle Data Modeller); relational model concepts working with database technologies; SQL, Oracle; non-relational systems such as NoSQL, MongoDB and Oracle NoSQL; an overview of Hadoop Technologies and introduction to Spark environment; database management and administration management of data; data governance; and data security. After studying this module, you will be able to apply a critical understanding of, and demonstrate ability in, the tools and techniques used in the development of database applications and understand the fundamental aspects of data governance and data security.
Human intelligence involves a continuous process of sensing, analysing, reasoning, and adaptation. In this course, you will focus on studying algorithms (both learning and optimisation), which could be used to develop an artificial intelligence (AI) system. You will focus in particular on theory and implementation using different programming languages. This module will provide you with opportunities to comprehend, define, and formulate real-world problems, integrate learning and optimisation algorithms such as artificial neural networks and genetic algorithms, and select optimal machine learning, training, and reasoning algorithms.
This module examines the protocols, architecture and devices that construct computer networks and how they are used to enable the internet to function. You will study operating systems and services, TCP/IP IPV6 network infrastructure, LANs and WANs WIFI, Bluetooth and mobile security, ACLs, firewalls and IPS systems and the architecture of the Internet. After studying this module, you will be able to demonstrate a deep understanding of the underpinning principles, practice and applications of networking and be able to use tools to simulate and evaluate different network designs.
In this module you will learn to use a wide variety of tools, techniques, methodologies and processes in the field of project management. Ethical and legal aspects of project planning and management will also be discussed. You will explore: project management and associated risks; risk handling techniques and methodologies; management of organisational resources and budgeting; legal, social, ethical and regulatory requirements and issues; planning, estimation, structure of projects; monitoring and control, review of scientific processes; and employability issues. You will develop a comprehensive understanding of the concepts of project management and its crucial operation in complex and unpredictable environments. By studying this module, you will develop a critical understanding of methodologies underpinning core project management processes and procedures to assure project success and minimise risk, and be able to flexibly and autonomously apply knowledge of solutions and processes that underpin professional practice in project management.
This module explores the concepts and practice of virtualisation and cloud computing. You will examine the solutions commonly used in these areas of industry and you will develop an understanding of the key aspects and principles of their operation. After studying this module, you will be able to demonstrate a critical understanding of the concepts, issues and considerations of virtualisation and cloud computing, and demonstrate mastery of the tools and advanced techniques used in the development of sophisticated solutions.
This module introduces you to research and methodologies used to underpin scientific work, data analysis, hypothesis establishment and artefact validation in understanding research of an appropriate subject discipline. The module explores: an introduction to research; literature search, discussion and critical evaluation; research methodologies and strategies; experimental procedures; data analysis methods; research philosophy; identification of a suitable project title; research impact and gap analysis; production of scientific work; consistency, rigour and clarity; ethics in research; and legal, social and regulatory requirements and issues. You will be actively engaged in enquiry during the learning process and have to articulate your own understanding of the issues examined during teaching sessions. You will understand the concepts of research and its crucial operation in complex and unpredictable environments where a range of techniques and technologies coexist to identify gaps in the existing literature. You will develop your collaborative abilities through the learning process as part of the task to cross-fertilise and discuss research ideas about the technologies analysed and their core implementation challenges and benefits with fellow students. You will be given the opportunity to select and examine specific research problems and to reflect and exercise research methods, title decomposition and research question formulations. By studying this module, you will develop a critical evaluation and understanding of knowledge on various research principles and methodologies and be able to flexibly and autonomously apply knowledge of solutions to open research problems, demonstrating the ability to understand research impact and develop gap analysis tools and techniques.
One of the most important skills expected of being an effective specialist in any discipline is the ability to work creatively under the appropriate guidance of an organisation. It is therefore essential that you use and develop the skills and knowledge gained from other modules and from your wider educational or working background in a major integrative exercise. In this module, you will be expected to develop an idea and demonstrate your ability to develop it further by applying your technical, analytical, practical and managerial skills in an integrated manner. This module will support you to autonomously develop your research skills and problem-solving skills to build a novel artefact that encompasses the theoretical domains and hands-on analysis and ideation during your course. You will engage in an informative tutorial on how to apply your knowledge from research methods in the design of your artefact and research questions. This module will enable you to demonstrate a deep and systematic understanding of a selected specialist area of your course, including issues at the forefront of research or professional practice in your chosen area. You will be able to independently design and undertake a substantial investigation that rigorously tackles a complex problem in computer science, selecting appropriate methodological processes and critically evaluating their effectiveness.
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