Computing (with Placement) MSc

Master

In Huddersfield

Price on request

Description

  • Type

    Master

  • Location

    Huddersfield

  • Duration

    18 Years

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.

Students studying this course will also be provided with access to the Chartered Management Institute (CMI) resources during their studies with us.

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.

Facilities

Location

Start date

Huddersfield (West Yorkshire)
See map
Queensgate, HD1 3DH

Start date

On request

About this course

This course is specifically aimed at International students, supporting those wishing to gain practical work based experiential learning. Together with studying your chosen course we are offering an additional 6 month placement opportunity, making the course 18 months in length. This allows students with limited experience to put into practice the skills and techniques developed throughout the Master’s degree.

100% of students from courses in this subject area go onto work and/or further study within six months of graduating.

Graduates from this course have gone on to roles such as Business Intelligent Consultants, Software Engineer, Technical Architect and Data Technician in organisations such as Capita, Mercedes-AMG, and Department of Health

An Honours degree (2:1 or above) in a Business Computing, Information Systems or IT (Information Technology) related subject or equivalent professional qualification
Applicants with other appropriate profession qualifications will be considered on an individual basis

This course is accredited by the British Computer Society (BCS), the Chartered Institute for the IT Industry. BCS accreditation is awarded to courses that provide a solid foundation in computing. It provides an indicator of quality to you and potential employers. Accreditation is independent recognition that this course meets the high standards set by the IT industry and meets industry needs.

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This centre's achievements

2019

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 13 years

Subjects

  • Access
  • Computing
  • IT Project Management
  • Data Mining
  • Design
  • Network
  • Database training
  • Database
  • Internet
  • Web
  • Project
  • Systems
  • Technology
  • Industry
  • Project Management
  • Visualisation
  • Network Training
  • Programming

Course programme

Core Modules

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.

Professional Development and Practice

This module provides students with the opportunity to reflect on their professional practice during their Masters degree by undertaking a period of development through study or by working with a company, research group or within a teaching environment in the UK or overseas. This module encourages students to reflect on their technical, personal and professional development experiences, and to identify their learning from these experiences.

Select one option module from:

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 module 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.

Teaching and Assessment

You will be taught through a series of lectures, tutorials, practical's in computer labs and independent study. Assessment will include coursework and peer review and reflect the emphasis of the course on the ability to apply knowledge and skills.

17% of the study time on this course is spent in lectures, seminars, tutorials etc.

Your module specification/course handbook will provide full details of the assessment criteria applying to your course.

Feedback (usually written) is normally provided on all coursework submissions within three term time weeks – unless the submission was made towards the end of the session in which case feedback would be available on request after the formal publication of results.

Computing (with Placement) MSc

Price on request