Advanced Computer Science

Attend a course fair How to apply
Attend a course fair How to apply


This course is aimed at Computing graduates who wish to specialise further in Computer Science improving their knowledge, understanding, skills and capabilities. Our postgraduate courses are concerned with vocational education, and it is anticipated that the majority of MSc graduates will either enter employment (or continue) as IT/Computing professionals, or progress to doctoral work with a probable view to pursuing academic or research careers.

You will study four specialist, advanced units including High Performance Computing and Big Data, Advanced Computer Networks and Operating Systems. A wide-range of optional units allow you to tailor your course to specialise in areas of your choice.

A third of your MSc will consist of a solo project with individual supervision. This is supported by a series of seminars/workshops, but the emphasis is on student-centred learning and recognises expectations about student autonomy, typical of postgraduate level and also is part of the strategy to enhance your employability through the development of confidence, self-awareness and self-sufficiency. Your Masters project will involve practical system creation or experimentation work in an area of computing and where appropriate, the implementation or experimentation may be work-based.

We are a member of the Oracle Academy and highly rated in terms of research. Our supervision and facilities are also excellent.

Students successfully completing this degree title will:

Non means-tested loans of up to a maximum of £10,000 will be available to postgraduate master’s students - click here to find out more information

Features and Benefits

Accreditations, Awards and Endorsements

Career Prospects

This course will equip you for a range of 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.

Learn more about graduate careers

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

Course details

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.

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.

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


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

Click below for unit information.

Read more about this year of study

Core Units

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 - 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 - Feature extraction and dimensionality reduction approaches.
  • Artificial Intelligence - Machine learning, AI approaches and their algorithms for handling big data e.g. images, graphs, text.
  • Models and Applications - Programming models and applications for big data and High-performance computing, including MPI, OpenMP, Hadoop/MapReduce, NoSQL with case studies.
  • Professional Context - Professional, legal, ethical, social and cultural issues in high performance computing of big data.
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. Topics include:

  • Wide area networks - 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 - 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 - Wireless links and network characteristics; WiFi: 802.11 Wireless LANs; Cellular internet access; IoT, Sensor networks.
  • Network Management - The Infrastructure for Network Management; The Internet-Standard Management Framework; Quality of Service; Performance and Planning.
  • Classic Operating Systems - Comparing the features and tradeoffs of classic operating systems;
  • Virtual Machines - Exploring the need for virtual machines and the means of their implementation;
  • File Systems - Looking at strengths and weaknesses of different approaches to persistent storage;
  • Distributed and Scalable Systems - Focusing on issues related to cloud computing and grid computing;
  • Concurrency, Scheduling & Sharing - Timing and scheduling, particularly in distributed systems;
  • Fault Tolerance - Looking at managing failure in distributed systems.
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; Shannons 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.

Enterprise Programming

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

  • Distributed computing development [25%] - eg RMI, JMS, JNDI, Jini, Connection to remote services (eg JDBC)
  • Use of a variety of distributed object programming methods [20%] - eg 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%]
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.

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.

Placements options

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

School of Computing, Mathematics and Digital Technology

Our School of Computing, Mathematics and Digital Technology is a vibrant community of staff and students, which prides itself on internal and external collaboration.

The department is committed to teaching and research that addresses societal challenges through disciplines like artificial intelligence, big data, computational fluid dynamics, cyber security, dynamical systems, the internet of things, smart cities, robotics and virtual reality.

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Taught by experts

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.

Meet our expert staff


UK and EU students

UK and EU students: Full-time fee: £8,500 per year. Tuition fees will remain the same for each year of your course providing you complete it in the normal timeframe (no repeat years or breaks in study).

Non-EU and Channel Island students

Non-EU international and Channel Island students: Full-time fee: £14,500 per year. Tuition fees will remain the same for each year of your course providing you complete it in the normal timeframe (no repeat years or breaks in study).

Additional Information

A Masters qualification typically comprises 180 credits, a PGDip 120 credits, a PGCert 60 credits, and an MFA 300 credits. Tuition fees will remain the same for each year of study provided the course is completed in the normal timeframe (no repeat years or breaks in study).

Part-time students may take a maximum of 90 credits each academic year.

Postgraduate Loan Scheme

Loans of up to £10,280 for many Postgraduate Courses

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Alumni Loyalty Discount

Rewarding our graduates

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How to apply

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.

You can review our current Terms and Conditions before you make your application. If you are successful with your application, we will send you up to date information alongside your offer letter.


Programme Review
Our programmes undergo an annual review and major review (normally at 6 year intervals) to ensure an up-to-date curriculum supported by the latest online learning technology. For further information on when we may make changes to our programmes, please see the changes section of our Terms and Conditions.

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. Please check back to the online prospectus before making an application to us to access the most up to date information for your chosen course of study.

Confirmation of Regulator
The Higher Education Funding Council for England is the principal regulator for the University. To find out more about the regulator’s role please visit their website.