Manchester Metropolitan University

MSc

Advanced Computer Science

2017 entry

Features and benefits of the course

  • The School has an extensive range of equipment in our own specialist laboratories which is supported by a dedicated team of technical staff.
  • Research in the School was rated 'internationally excellent' with some rated 'world-leading' in the 2014 Research Excellence Framework (REF).
  • Our online virtual learning platform Moodle, provides access to lectures, course materials and assessment information.
  • Classes are concentrated on certain days of the week to facilitate part-time students’ attendance and allow full-time students to undertake part-time employment if necessary.
  • The School of Computing, Mathematics and Digital Technology is a member of the Oracle Academy.
  • We are an academic partner of the Institute of Information Security Professionals (IISP). This partner status recognises our expertise in the field of information and cyber security.
  • We are also an Academy of the Computer Technology Industry Association (CompTIA) and deliver their partner programme which provides a pathway for students towards a rewarding, high-growth IT career.

Accreditations, Awards and Endorsements

Placement options

Some students undertake practical work for their projects while working in organisations which have offered placement opportunities.

About the course

Wide-ranging course units combine with a flexible approach which allows students to undertake practical project work while attending work placements. With one-third of the course project-based, it may be possible to undertake yours in collaboration with an external organisation or within the School. The part-time route is especially suitable if you have industrial experience and wish to update your knowledge. Especially useful in the case of missed classes, the online virutal learning environment, Moodle, provides extensive access to lectures, course materials and assessment information.

Read a graduate profile: Meet David, Yvonne and Karen.

Our Research in Informatics

Manchester Metropolitan University’s School of Computing, Mathematics and Digital Technology is home to the Informatics Research Centre (IRC), an interdisciplinary hub that conducts leading work on fundamental and applied computer science. Areas of research include intelligent systems, image and sensory computation, logic, peer-to-peer computing, computation, novel and natural computing, informatics and computational fluid dynamics. Research in the School was rated ‘internationally excellent’ with some rated ‘world-leading’ in the 2014 Research Excellence Framework.

The Centre is characterised by its distinctive mix of expertise, research strengths and cross-discipline working. Its over-arching aim is to use computer science to address societal challenges and ensure research has significant impact in areas such as healthcare, future cities and security.

Typical units of study may include

Year 1

This course can be taught full-time over 1 year, or part-time 3 years. If taught full-time all units will be taken within 1 year.

  • High performance Computing and Big Data
  • Advanced Computer Networks and Operating Systems
  • Masters Project

Options

  • Introduction to Data Science
  • Enterprise Programming
  • Mobile and Ubiquitous Computing
  • Cryptography and Encryption
  • Data Management and Machine Learning

Click below for unit information.

Core Units
Advanced Computer Networks and Operating Systems

The unit covers advanced topics in computer networks and operating systems. It focuses on principles, architectures, and protocols used in modern large scale networked systems.

  • Wide area networks [10%] - Compare the characteristics of WAN technologies, including their switching type, throughput, media, security, and reliability; Describe several WAN transmission and connection methods.
  • Virtual networking and remote access [10%] - Explain virtualization and identify characteristics of virtual components; Understand VPNs (virtual private networks) and the protocols they rely on; Identify the features and benefits of cloud computing and NaaS (network as a service).
  • Wireless and mobile networking [20%] - Wireless links and network characteristics; WiFi: 802.11 Wireless LANs; Cellular internet access; IoT, Sensor networks.
  • Network Management [10%] - What Is Network Management? The Infrastructure for Network Management; The Internet-Standard Management Framework; Quality of Service; Performance and Planning.
  • Classic Operating Systems [5%] - Comparing the features and tradeoffs of classic operating systems;
  • Virtual Machines [10%] - Exploring the need for virtual machines and the means of their implementation;
  • File Systems [10%] - Looking at strengths and weaknesses of different approaches to persistent storage;
  • Distributed and Scalable Systems [10%] - In particular, focusing on issues related to cloud computing and grid computing;
  • Concurrency, Scheduling & Sharing [10%] - Timing and scheduling, particularly in distributed systems;
  • Fault Tolerance [5%] - Looking at managing failure in distributed systems.
High Performance Computing and Big Data

The aim of this unit is to develop students' knowledge in the areas of parallel and distributed processing, machine learning approaches for handling big data  and current parallel programming models for high-performance computing and big data processing, such as  MPI and MapReduce.

  • Current and Emerging Trends [25%] - Evaluation  of current and emerging trends underpinning parallel and distributed systems for high-performance computing and big data – paradigms and platforms,  cloud computing.
  • Features of Big Data [10%] - Feature extraction and dimensionality reduction approaches.
  • Artificial Intelligence [10%] - Machine learning, AI approaches and their algorithms for handling big data e.g. images, graphs, text.
  • Models and Applications [50%] - Programming models and applications for big data and High-performance computing, including MPI, OpenMP, Hadoop/MapReduce, NoSQL with case studies.
  • Professional Context [5%] - Professional, legal, ethical, social and cultural issues in high performance computing of big data.
Masters Project

This unit will involve practical system creation or experimentation work in an area of computing other than digital media. The curriculum is specific to the project you choose but it will include seminars on skills and techniques required for successful design and implementation of research resources, time management, research presentation (oral, written, posters) and professional, legal and ethical issues in computing. Examination of a case study or project in an area appropriate to your intended dissertation work. Where appropriate, the implementation or experimentation may be work-based.

Likely Optional Units
Cryptography and Encryption

The unit covers theoretical discussion of the key encryption algorithms: Diffie-Hellman, RSA, Digital Signatures, modern symmetric cryptosystems DES and AES. Additionally we will code the algorithms and their variants in a modern programming language and implement cryptosystems over a computer network.

Classical Cryptography; Shannon’s Theory; Block Ciphers; Hash Functions; RSA Algorithm and variants; Discrete and Public-Key Algorithms; Signatures; Pseudo-random number generators; Identification Schemes and Entity Authentication; Key Distribution; Key Agreement Schemes.

Data Management and Machine Learning

The aim of this unit is to develop the student’s knowledge in the areas of  data management including online analytical processing; data architectures such as data warehousing and the process and application of machine learning algorithms to data.

  • Data Management Overview [15%] - Example content includes database modelling/querying (relational/noSQL), graph data modelling, applications.
  • Online Analytical Processing (OLAP) [15%] - Including the representation of multi-dimensional views of data; Technologies and Architectures; Categories of OLAP tools, Business Intelligence Tools.
  • Data Warehousing [10%] - Methodologies, architectures, modelling techniques; Data Warehousing Project Management; The Extraction, Transformational and Loading Process;
  • Machine Learning Overview [10%] - The machine learning process, Applications of machine Learning.
  • Machine Learning Algorithms [50%] - For example, artificial neural networks, naïve bayes, decision  trees, clustering, association rules, text mining,fuzzy systems. application, analysis and validation.
Enterprise Programming

Examines key aspects of Distributed Programming and Software Engineering aspects of Enterprise level applications.

  • Distributed computing development [25%] - e.g. RMI, JMS, JNDI, Jini, Connection to remote services (eg JDBC).
  • Use of a variety of distributed object programming methods [20%] - e.g. Web Services, REST, SOAP, Ajax, Spring Framework
  • Object wrapping formats and APIs [10%] - e.g. XML, JSON etc.
  • Cloud based software development [20%] - e.g. PAAS, SAAS, IAAS
  • Design Patterns, Refactoring, SE design techniques [25%]
Mobile and Ubiquitous Computing

Provides an understanding of the issues, technologies and concepts in mobile and ubiquitous infrastructures, particularly in wireless networks, context-awareness, sensors and programming mobile devices.

  • Explore and evaluate mobile application development frameworks and tools: [50%]
  • Principles in wireless communications: [5%]
  • Research and practise in context and location awareness: [15%]
  • Interfacing to sensors: [15%]
  • Resource discovery and system configuration: [5%]
  • Design of pervasive computing systems: [5%]
  • Examining the literature related to the subject matter: [5%]

Programme Review

Each programme of study that we offer undergoes an annual review to ensure an up-to-date curriculum supported by the latest online learning technology. In addition, we undertake a major review of the programme, normally at 6-yearly intervals, but this can take place at a more frequent interval where required. Applicants should note that the programme currently provided may be subject to change as a result of the review process. We only make changes where we consider it necessary to do so or where we feel that certain changes are in the best interests of students and to enhance the quality of provision. Occasionally, we have to make changes for reasons outside our control. Where there are changes which may materially affect the current programme content and/or structure, offer holders will be informed.

Assessment details

Assessment will be through coursework, examination and dissertation.

Additional Information About this Course

Students are expected to behave in a professional and business like manner when on placement or conducting projects with external partners.

Teaching Staff

Your studies are supported by a team of committed and enthusiastic teachers and researchers, experts in their chosen field. We also work with external professionals, many of whom are Manchester Met alumni, to enhance your learning and appreciation of the wider subject. Details of departmental staff can be found at: http://www.scmdt.mmu.ac.uk/our-staff/

Typical entry requirements

You will normally have at least a second-class UK Honours degree (or international equivalent) in a computing-related subject, or exceptionally, a good sub-degree qualification in computing and very substantial work experience in computing or a closely-related area.

International students please see mmu.ac.uk/international

There’s further information for international students on our international website if you’re applying with non-UK qualifications.

How do I apply for this course?

The quickest and most efficient way to apply for this course is to apply online. This way, you can also track your application at each stage of the process.

Apply online now

If you are unable to apply online, you can apply for full- and part-time taught courses by completing the postgraduate application form. There are exceptions for some professional courses – the course information on our on-line prospectus will give you more information in these cases.

Please note: to apply for this course, you only need to provide one reference.

Career options after the course

This course will equip you for a range of IT positions in the private and public sectors and is also a good foundation for further study. Our MSc graduates have entered a wide range of industries or gone onto PhDs, including in the School of Computing, Mathematics and Digital Technology.

Careers support is available from the moment you join us, throughout your time here, and for up to three years after the completion of your course. We have a range of services available through the School of Computing, Mathematics and Digital Technology and the University Careers Service including dedicated careers and employability advisors.

Professional Accreditation

The School is an educational affiliate of the British Computing Society – the Chartered Institute for IT in the UK (BCS), a member of the Oracle Academy and an Academy for the Computer Technology Industry Association. Many of the School’s degree programmes are accredited by BCS.

The School is also an academic partner of the Institute of Information Security Professionals who recognise our expertise in the field of information and cyber security. Mathematics degree courses are approved by the Institute of Mathematics and its Applications.

Confirmation of Regulator

The Higher Education Funding Council for England is the principal regulator for the University.

Important Notice

This online prospectus provides an overview of our programmes of study and the University. We regularly update our online prospectus so that our published course information is accurate and up to date. Please note that our programmes are subject to review and development on an ongoing basis. Changes may sometimes be necessary. For example, to comply with the requirements of professional or accrediting bodies or as a result of student feedback or external examiners’ reports. We also need to ensure that our courses are dynamic and current and that the content and structure maintain academic standards and enhance the quality of the student experience.

Please check back to the online prospectus before making an application to us.

The provision of education by the University is subject to terms and conditions of enrollment and contract. The current Terms and Conditions Applicable to the provision of the University’s Educational Services are available online. When a student enrolls with us, their study and registration at the University will be governed by various regulations, policies and procedures. It is important that applicants/students familiarize themselves with our Terms and Conditions and the Key Contract Documents referred to within. Applicants will be provided with access to an up to date version at offer stage. This can be found within the Information for Offer Holders document.