Save this page
Save this page

My Saved Pages

  • Saved page.

My Saved Courses

  • Saved page.
Reset

Recently visited

  • Saved page.

MScAdvanced Computer Science with Big Data

Why this course?

Get ahead with a career in data science or analytics with the MSc Advanced Computer Science with Big Data

Big data is of growing importance in businesses and society in general. A skills shortage in this area means companies are willing to pay high salaries for the right skill set (The Guardian Career Choices).

Opportunities for graduates exist in a range of industries such as finance, films and games, pharmaceuticals, health care, consumer products and public services.

You’ll study

Our MSc Advanced Computer Science with Big Data gives you the skill set needed. You'll choose leading classes that span the breadth of both computer and information sciences, including:

  • theoretical computer science
  • human-computer interaction
  • information sciences
  • software engineering
  • machine learning
  • big data technologies

You'll gain an understanding of the new challenges posed by the big data revolution, particularly in relation to its modelling, storage and access.

You'll understand key algorithms and techniques embodied within data analytics solutions and be exposed to a number of different big data technologies and techniques.  You’ll see how they can achieve efficiency and scalability, while also addressing design trade-offs and their impacts.

You'll learn key technologies that are at the heart of big data analytics such as:

  • NoSQL databases
  • Hadoop
  • Map-Reduce programming paradigm

You'll also be equipped with a sound understanding of the principles of machine learning and a range of popular approaches, along with the knowledge of how and when to apply these.

On this Masters course you’ll also have the opportunity to implement and experiment with these machine learning algorithms using the most popular languages such as R and Python, explore their applications to areas as diverse as analysing activity-related data captured using a smartphone to financial time-series prediction.

Project

You’ll take on an exciting individual research project with one of our industrial partners. Performing cutting-edge research and development, you’ll pursue a specific interest in further depth, giving scope for original thought, research and technical presentation of complex ideas. 

Course content

Compulsory classes

Legal, ethical and professional issues for the information society

The aim of this class is:

  • to appreciate the characteristics of professionalism as it relates to modern data management
  • to recognise and appreciate the professional aspects of other engineering and related classes in their curriculum, and how those aspects influence practice
  • to form a sound basis on which they will subsequently be able to practise
  • information Systems Engineering with a due regard for legal, ethical and social issues
Distributed Information Systems
This class will give you an extended understanding of the deep, technical issues underlying information systems in the particular context of distributing content over the world-wide web.         
Big Data Technologies

The aim of the class is to:

 

  • understand the fundamentals of Python to enable the use of various big data technologies
  • understand how classical statistical techniques are applied in modern data analysis
  • understand the potential application of data analysis tools for various problems and appreciate their limitations;
  • be familiar with a number of different cloud NoSQL systems and their design and implementation, showing how they can achieve efficiency and scalability, while also addressing design trade-offs and their impacts
  • be familiar with the Map-Reduce programming paradigm, to enable students to write programs which can execute in massively parallel cloud-based infrastructures

 

Machine Learning for Data Analytics

The aim of the class is to:

  • understand the aims and fundamental principles of machine learning
  • understand a range of the key algorithms and approaches to machine learning
  • be able to apply the algorithms covered and interpret the outcomes
  • understand the applicability of the algorithms to different types of data and problems along with their strengths and limitations
Research project

Cutting-edge research and development project at one of our industrial partners. This might involve developing or validating a test setup, characterising a product, raw materials, instrumentation or vendor parts, improving the performance of a product or process, or participating in research and development of a new technology or product.

Elective classes

Choose two from the following:

Advanced Topics in Software Engineering

This class aims to:

  • make students aware of key aspects of current software engineering research
  • familiarise students with the state-of-the-art in terms of what problems can be solved and what are the current exciting challenges
  • develop the necessary skills in students to allow them to contribute to the software engineering research community
  • equip students with the skills and background to appreciate the contributions to software engineering research across the full range of material presented at the key international conferences in the field
Mobile Software Applications

You'll develop an understanding of the theories, paradigms, algorithms and architectures for building software applications to function in mobile computing environments.                     

Evolutionary Computing for Finance

On completion of this class students will:

  • gain an understanding of a range of evolutionary computational and machine learning techniques
  • gain an understanding of the relative advantages and disadvantages of each technique for different financial applications
  • be able to evaluate the results of a financial problem investigated using evolutionary computation and machine learning techniques

Learning & teaching

Teaching methods include lectures, tutorials and practical laboratories. Dissertation is by supervision.

You’ll also have the opportunity to meet industry employers and participate in recruitment events.

Entry requirements

  • minimum second class honours degree or international equivalent in computer science or another numerate discipline (e.g. mathematics, physics, engineering)
  • some programming or database experience is normally a requirement
  • other disciplines who have significant programming experience should contact us to discuss applying for this course

English language requirements

You must have an English language minimum score of IELTS 6.0 (with no component below 5.5).

We offer comprehensive English language courses for students whose IELTS scores are below 6.0. Please see ELTD for full details.

Pre-Masters preparation course

The Pre-Masters Programme is a preparation course held at the University of Strathclyde International Study Centre, for international students (non EU/UK) who do not meet the academic entry requirements for a Masters degree at University of Strathclyde. The Pre-Masters programme provides progression to a number of degree options.

Upon successful completion, you will be able to progress to this degree course at the University of Strathclyde.

Fees & funding

2019/20

All fees quoted are for full-time courses and per academic year unless stated otherwise.

Scotland/EU

  • £8,100

Rest of UK

  • £8,100

International

  • £17,350

How can I fund my course?

Scottish and non-UK EU postgraduate students

Scottish and non-UK EU postgraduate students may be able to apply for support from the Student Awards Agency Scotland (SAAS). The support is in the form of a tuition fee loan and for eligible students, a living cost loan. Find out more about the support and how to apply.

Don’t forget to check our scholarship search for more help with fees and funding.

Students coming from England

Students ordinarily resident in England may be to apply for postgraduate support from Student Finance England. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.

Don’t forget to check our scholarship search for more help with fees and funding.

Students coming from Wales

Students ordinarily resident in Wales may be to apply for postgraduate support from Student Finance Wales. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.

Don’t forget to check our scholarship search for more help with fees and funding.

Students coming from Northern Ireland

Postgraduate students who are ordinarily resident in Northern Ireland may be able to apply for support from Student Finance Northern Ireland. The support is a tuition fee loan of up to £5,500. Find out more about the support and how to apply.

Don’t forget to check our scholarship search for more help with fees and funding.

International students

We have a large range of scholarships available to help you fund your studies. Check our scholarship search for more help with fees and funding.

Please note

The fees shown are annual and may be subject to an increase each year. Find out more about fees.

Careers

Opportunities for graduates of the MSc Advanced Computer Science with Big Data exist in various industries:

  • finance
  • films and games
  • pharmaceuticals
  • healthcare
  • consumer products
  • public services

Future career options include:

  • big data analyst
  • software engineer
  • data scientist
  • data consultant

Graduate salaries*

CareerGraduate salary
Data scientist  £19,000 to £25,000 
Data analyst £24,000 - £30,000 
Software engineer £18,000 

*Data taken from Prospects (last accessed 8 October 2018)

Contact us

Apply

Advanced Computer Science with Big Data

Qualification: MSc, Start date: Sep 2019, Mode of delivery: attendance, full-time

Discover more about Strathclyde