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In the programme the student has to take 6 Mandatory modules (30 ECTS) and 2 electives (10 ECTS). In addition to taught modules the student will have to complete a research project (20 ECTS). Further detail on these modules are outlined below. All modules are 5 ECTS unless indicated.

Mandatory Modules
Cloud Strategy Planning & Management (M) This module will enable students to evaluate the strategic value of cloud computing as part of a Information Technology (IT) strategy and will give students the skills and knowledge to plan and manage a cloud computing strategy for an organisation.
Managing Virtual Environments (M) In this module, students will learn how to create, configure, troubleshoot and automate the provisioning of a virtualised environment, which is essentially a software based IT infrastructure that is distributed as a service using the Infrastructure as a Service (IaaS) delivery model in cloud computing.
Cloud Storage Infrastructures (M) This module provides a comprehensive view of storage infrastructure for cloud based virtualised systems enabling IT-as-a-Service solutions. Cloud storage is a service model in which data is maintained, managed, backed up remotely and made available to users on-demand over a network as a shared pool of configurable storage that can be rapidly provisioned and released. As part of this module the student will learn how to create and manage storage for a virtualised data centre and cloud environment.
Data Centre Networking (M) Data Centres are critical to the success of Cloud Computing. More and more Data Centres are being built due to immense growth in data volumes, internet connected devices, and applications/services. These Data Centres are delivering unprecedented levels of computing density and energy efficiency. This module covers the key technologies in modern Data Centre Networking.
Cloud Security (M) If a cloud computing system is not secure, then as a concept it is doomed to fail. This module addresses the security issues that pertain to cloud computing as well as best practices, tools and approaches to ensure that the virtualised infrastructure, data and applications are protected.
Computing Research & Practice (M) The purpose of this module is to introduce students to the tools and techniques for doing research. In this module the nature of research will be examined and the methods to undertake investigations across a broad range of subjects presented. On completion of this module students will have identified a research topic and developed a research proposal outlining the context of the topic, its research aims, objectives, methodologies, work plan etc.
(The electives indicated below are a sample set that could be offered in any given semester)

Scalable Microservices (E)

This elective module is specifically developed for software developers who are participating in the programme.

Over the past number of years, a new paradigm for software architecture has emerged, referred to as microservices. Microservices are singular in terms of their responsibility and can be independently scaled, tested and deployed. Services developed using this approach are built around business capabilities using best practices from domain-driven-design and are autonomous and isolated. In this module the student will learn a framework technology and using this framework will develop skills to build, automate, scale and manage a distributed system created from a number of collaborating components represented as microservices.
Scripting for System Automation (E) The continued push towards automating not just the software development process but also infrastructure management has greatly increased the efficiency of modern software organizations. It has also led to some of the responsibility for such automation shifting from system administrators to developers, empowered by many new 'DevOps' tools. This module will address the scripting skills that system administrators, developers and testers need to automate tasks in development, operations and infrastructure management.
Data Analytics (E) Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is used in many industries to allow companies and organizations to make better business decisions and in the sciences to verify or disprove existing models or theories. Data analytics is distinguished from data mining by the scope, purpose and focus of the analysis. Data analytics focuses on inference, the process of deriving a conclusion based solely on what is already known by the researcher. This module explores the most recent trends in this fast growing field.
Future Internet (E) The interconnection of smart objects and "things" is driving the Internet to the edge of its architectural capability and capacity and are creating new engineering requirements for the Internet. However, the ossification of the Internet has to date prevented it from meeting these requirements as stakeholder agreement is required before any change can be applied over the Internet's network of networks. This module will discuss the challenges and driving forces behind the Future Internet (FI) and enabling technologies behind its development.


In addition to the above in order to fulfill the requirements for the award the student must complete a project and dissertation. This project is 20 ECTS and further information on this module is indicated below.

Computer Science Project Implementation (M) (20 ECTS) Prior to completing this module the student through the employment of various research methods and selected practices will have identified their chosen research question. As part of this module, the student will complete their research project and implementation relevant to their field or domain of expertise. The student will be expected to disseminate the research work and outcomes through an oral/poster presentation and submission of a dissertation.