Computing MSc

2019-20 (also available for 2020-21)

This course is eligible for Master's loan funding. Find out more.

Start date

16 September 2019

13 January 2020

Duration

1 year full-time

Places available (subject to change)

20

Phone contact: +44 (0)1484 473116

About the course

Today organisation’s critical work systems are linked to the information technology (IT) that supports them. The growth of the internet and mobile industries as IT environments for commercial transaction and information exchange has placed additional burdens on IT teams in organisations, requiring that developers be aware both of the infrastructure of the internet/mobile networks and the enabling web/mobile technologies.

The deployment of software systems on intranets and the internet is now of significant demand in the computing field and developers and IT managers must have the higher skills to deliver complete, robust hardware and software solutions for these environments.

This perspective reflects the view adopted by employers in the IT industry who seek to recruit people that have the required technical competence in the field of applied IT.

The course has been designed to equip computing graduates and professionals with the advanced knowledge and skills to analyse, model, design, develop, implement and evaluate computer-based systems in a wide range of application environments.

Course detail

Semantic Web

This module will cover basic ontology languages, semantic modelling, linked data principles, semantic query languages and basic reasoning methods for processing semantic data. Working both individually and in teams, you will be introduced to industry practice.

Autonomous and Autonomic Intelligent Systems

Autonomous systems are intelligent systems that can act independently to accomplish goals based on their knowledge and understanding of their environment and the tasks they have to complete. This module aims to cover the background and requirements for intelligent systems autonomy in a wide range of applications, taken from a computer science and software-oriented viewpoint. As well as the technical challenges of system autonomy, you’ll get the opportunity to study ethical and legal issues, and human factors implications.

Web and Network Services

This module considers how the Internet can be used to provide services, such as the web enabled provision of information, cloud computing and VoIP (Voice over Internet Protocol). As well as providing a service the Internet can also be used as a medium for the control of remote agents, such as robotic devices, and within this you’ll consider the technologies that facilitate the provision of remote access control. This module also provides you with the opportunity to to explore contemporary research areas regarding Internet related subjects.

Effective Research and Professional Practice

This module aims to provide you with skills that are key to helping you become a successful computing researcher or practitioner. You'll get the opportunity to study topics including the nature of research, the scientific method, research methods, literature review and referencing. The module aims to cover the structure of research papers and project reports, reviewing research papers, ethical issues (including plagiarism), defining projects, project management, writing project reports and making presentations.

Individual Project

This module enables the student to work independently on a project related to a self-selected problem. A key feature in this final stage of the MSc is that students will be encouraged to undertake an in-company project with an external Client. Where appropriate, however, the Project may be undertaken with an internal Client - research-active staff - on larger research and knowledge transfer projects. The Project is intended to be integrative, a culmination of knowledge, skills, competencies and experiences acquired in other modules, coupled with further development of these assets. In the case where an external client is involved, both the Client and Student will be required to sign a learning agreement that clearly outlines scope, responsibilities and ownership of the project and its products or other deliverables. The Project will be student-driven, with the clear onus on the student to negotiate agreement, and communicate effectively, with all parties involved at each stage of the Project.

Select one option module:

Parallel Computer Architectures Cluster and Cloud Computing

Many existing and future computer-based applications impose exceptional demands on performance that traditional predominantly single-processor systems cannot offer. Large-scale computational simulations for scientific and engineering applications now routinely require highly parallel computers. In this module you will learn about Parallel Computer Architectures, Legacy and Current Parallel Computers, trends in Supercomputers and Software Issues in Parallel Computing; you will be introduced to Computer Cluster, Cloud and Grid technologies and applications. You will study the fundamental components of Cluster environments, such as Commodity Components for Clusters, Network Services/Communication software, Cluster Middleware, Resource management, and Programming Environments. The module is assessed by examination (60%) and practical assignment based on laboratory work (40%).

Data Mining

Data mining is a collection of tools, methods and statistical techniques for exploring and extracting meaningful information from large data sets. It is a rapidly growing field due to the increasing quantity of data gathered by organisations. There is a potential high value in discovering the patterns contained within such data collections. This module looks at different data mining techniques and gives students the chance to use appropriate data-mining tools in order to evaluate the quality of the discovered knowledge. Topics studied include looking at the value of data; approaches to preparing data for exploration; supervised and un-supervised approaches to data mining; exploring unstructured data; social impact of data mining. Current application areas and research topics in data mining will also be discussed and students will be expected to develop their knowledge such that they are able to contribute to such discussions and to increase their background knowledge and understanding of issues and developments associated with data mining.

Big Data Analytics

The ever-increasing advancements in sensing technologies, network infrastructure, storage and social media have enabled us to acquire an unprecedented volume of data at an explosive rate. As a result, the ability to efficiently and accurately derive human-understandable knowledge from these datasets has become increasingly critical to our digitally-driven society and economy. Under this Big Data phenomenon, tremendous endeavours have been devoted to tackle its underlying challenges through both novel solutions and the evolution of existing methodology. The module aims to provide students with the knowledge and critical understanding of contemporary challenges posed by the big data. The topics covered here include the fundamental characteristics and operations associated with big data; existing and emerging architectures and processing techniques; domain applications of big data in practice. Through this module, students will develop an informed understanding of the principles and practice of big data analytics in both general and application specific contexts.

Select one option module from:

Advanced Software Development

You’ll be provided with the opportunity to develop advanced skills in software design and development. You’ll have the opportunity to examine the issues that software programmers and developers face every day in their quest to develop successful technology systems and applications.

Software Development

This module brings together database, object-oriented semantics and web authoring skills using an appropriate set of development tools to enable the student to construct distinct software artefacts. The module provides an introduction to the programming and design techniques used to produce information systems that meet their required specifications. This will involve the modelling of business activity, the information that supports decision making and instances of significant events and actions. Student will acquire skills in programming languages capable of implementing object-oriented and web script software and will also be able to select and apply design techniques to enable an appropriate choice of semantic components and implemented software components to meet the requirements of a given software system.

Select two option modules from:

Change and Project Management

This module aims to cover planning for different types of change – discontinuous, radical, incremental or continuous, focusing on both the human and organisational impacts of these changes. As a manager it’s important for you to be able to incorporate management theory and concepts within your working practice. This module aims to help you understand how planning and project management provide opportunities for you to manage change more effectively and efficiently. You’ll have the opportunity to study project management methods, tools and techniques as well as developing an understanding of risk.

Data Visualisation

With ever-increasing advancements in Internet-of-Things, Cyber-Physical Systems, and social media applications huge volume of complex and multi-dimensional datasets are being generated every day. Visually analysing these datasets facilitates the transformation of raw data into valuable knowledge and information. The biggest challenge is to articulate suitable solutions of complex analytical problems by visually interacting with the designed artefacts without going into underlying complexities. Tremendous endeavours have been devoted to streamline innovative solutions, novel methods, tools, processes and methodologies to address underlying challenges. This module aims to provide students with core knowledge and deep understanding of advanced theories underpinning data visualisation, best practices in using visualisation artefacts effectively and practical skills in implementing the theoretical knowledge into certain application domains. Students will be engaged in practical utilisation of state-of-the-art visualisation tools and methods to understand real-world big data problems, and to rectify complex issues with visual analysis. Topics that will be covered in this module include exploratory data visualisation; data visualisation theories, existing and emerging interactive 2D and 3D visualisation toolkits, and application of visualisation skillset in application specific domains.

Databases for Large Data-sets

The data needs of modern Enterprises and organisations require a more flexible approach to data management than that offered by traditional relational database management systems (RDBMS). With organizations increasingly looking to Big Data to provide valuable business insights, it has become clear that new approaches are required to handle these new data requirements. Primarily focusing on non-relational data models, this module introduces students to alternative approaches to modelling the data needs of an organization. It also provides students with an opportunity to use non-relational databases and database technologies to build robust and effective organizational information systems. The aim of this module is to introduce the student to the fundamental concepts, core principles, formalism, and practical skills that underpin modern data system where students will develop a practical understanding of methods, techniques and architectures required to build big data systems in order to extract information from large heterogeneous data sets.

Machine Learning

Machine Learning techniques are now used widely in a range of applications either stand-alone or integrated with other AI techniques. The Machine Learning module allows you to obtain a fundamental understanding of the subject as a whole: how to embody machines with the ability to learn how to recognise, classify, decide, plan, revise, optimise etc. You will learn which machine learning techniques are appropriate for which learning problem, and what the advantages and disadvantages are for a range of ML techniques. We will consider the widely known data-driven approaches, and specific techniques such as “deep learning”, and investigate the typical applications and potential limitations of these approaches. We will introduce available tools and use them in practical classes, evaluating learning bias and characteristics of training sets. High profile applications of data driven, stand-alone, ML systems will be investigated, such as the AlphaGo method. Where data is sparse, and knowledge is already present in a system, we will investigate methods to improve heuristics of existing AI systems, and to learn or revise domain knowledge. This is essentially the area of model-driven ML, where the learning system is often integrated to other reasoning systems.

You will need to complete all modules to progress onto the Individual Project. The course includes the following:

Entry requirements

Entry requirements for this course are normally:

  • An Honours degree (2:2 or above) in business computing/IS/ICT-related subject or an equivalent professional qualification.
  • Other qualifications and/or experience that demonstrate appropriate knowledge and skills at an Honours degree level.
  • Substantial (3 years) relevant industry experience in a management role.

If your first language is not English, you will need to meet the minimum requirements of an English Language qualification. The minimum for IELTS is 6.0 overall with no element lower than 5.5, or equivalent will be considered acceptable. Read more about the University’s entry requirements for students outside of the UK on our Where are you from information pages.

Teaching excellence

Research plays an important role in informing all our teaching and learning activities.Through research our staff remain up-to-date with the latest developments in their field, which means you develop knowledge and skills that are current and highly relevant.

For more information see the Research section of our website.

  1. Huddersfield is a TEF gold-rated institution delivering consistently outstanding teaching and learning of the highest quality found in the UK (Teaching Excellence Framework, 2017).

  2. We won the first Global Teaching Excellence Award recognising the University’s commitment to world-class teaching and its success in developing students as independent learners and critical thinkers (HEA, 2017).

  3. Here at Huddersfield, you’ll be taught by some of the best lecturers in the country. We’ve been the English university with the highest proportion of professionally-qualified teaching staff for the past four years*.

  4. We are one of the four leading institutions in the country for National Teaching Fellowships, which rate Britain’s best lecturers. It's part of our drive for teaching excellence, which helps you to achieve great things too.

  5. All our permanent teaching staff** have, or are completing, doctorates. This expertise, together with our teaching credentials, means that students here learn from knowledgeable and well-qualified teachers and academics who are at the forefront of their subject area.

*HESA - First awarded in 2016, maintained in 2017, 2018 and 2019.

**Permanent staff, after probation: some recently appointed colleagues will only obtain recognition in the months after their arrival in Huddersfield, once they have started teaching; research degrees applies to those on contracts of more than half-time.

Student support

At the University of Huddersfield, you'll find support networks and services to help you get ahead in your studies and social life. Whether you study at undergraduate or postgraduate level, you'll soon discover that you're never far away from our dedicated staff and resources to help you to navigate through your personal student journey. Find out more about all our support services.

Important information

We will always try to deliver your course as described on this web page. However, sometimes we may have to make changes as set out below.

Changes to a course you have applied for

If we propose to make a major change to a course that you are holding an offer for, then we will tell you as soon as possible so that you can decide whether to withdraw your application prior to enrolment.

Changes to your course after you enrol as a student

We will always try to deliver your course and other services as described. However, sometimes we may have to make changes as set out below:

Changes to option modules

Where your course allows you to choose modules from a range of options, we will review these each year and change them to reflect the expertise of our staff, current trends in research and as a result of student feedback or demand for certain modules. We will always ensure that you have a range of options to choose from and we will let you know in good time the options available for you to choose for the following year.

Major changes

We will only make major changes to the core curriculum of a course or to our services if it is necessary for us to do so and provided such changes are reasonable. A major change in this context is a change that materially changes the services available to you; or the outcomes, or a significant part, of your course, such as the nature of the award or a substantial change to module content, teaching days (part time provision), classes, type of delivery or assessment of the core curriculum.

For example, it may be necessary to make a major change to reflect changes in the law or the requirements of the University’s regulators; to meet the latest requirements of a commissioning or accrediting body; to improve the quality of educational provision; in response to student, examiners’ or other course evaluators’ feedback; and/or to reflect academic or professional changes within subject areas. Major changes may also be necessary because of circumstances outside our reasonable control, such as a key member of staff leaving the University or being unable to teach, where they have a particular specialism that can’t be adequately covered by other members of staff; or due to damage or interruption to buildings, facilities or equipment.

Major changes would usually be made with effect from the next academic year, but this may not always be the case. We will notify you as soon as possible should we need to make a major change and will carry out suitable consultation with affected students. If you reasonably believe that the proposed change will cause you detriment or hardship we will, if appropriate, work with you to try to reduce the adverse effect on you or find an appropriate solution. Where an appropriate solution cannot be found and you contact us in writing before the change takes effect you can cancel your registration and withdraw from the University without liability to the University for future tuition fees. We will provide reasonable support to assist you with transferring to another university if you wish to do so.

Termination of course

In exceptional circumstances, we may, for reasons outside of our control, be forced to discontinue or suspend your course. Where this is the case, a formal exit strategy will be followed and we will notify you as soon as possible about what your options are, which may include transferring to a suitable replacement course for which you are qualified, being provided with individual teaching to complete the award for which you were registered, or claiming an interim award and exiting the University. If you do not wish to take up any of the options that are made available to you, then you can cancel your registration and withdraw from the course without liability to the University for future tuition fees and you will be entitled to a refund of all course fees paid to date. We will provide reasonable support to assist you with transferring to another university if you wish to do so.

When you enrol as a student of the University, your study and time with us will be governed by a framework of regulations, policies and procedures, which form the basis of your agreement with us. These include regulations regarding the assessment of your course, academic integrity, your conduct (including attendance) and disciplinary procedure, fees and finance and compliance with visa requirements (where relevant). It is important that you familiarise yourself with these as you will be asked to agree to abide by them when you join us as a student. You will find a guide to the key terms here, along with the Student Protection Plan, where you will also find links to the full text of each of the regulations, policies and procedures referred to.

The Office for Students (OfS) is the principal regulator for the University.

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