MSc Big Data (Online)

This is a two year online course designed to equip you with skills in big data technology, advanced analytics and industrial and scientific applications that will lead to a job in in the growing data science or analytics fields.

Big Data (Online)

Key facts

  • Award Masters / MSc
  • Start date October 2021, February 2022, May 2022, October 2022, February 2023, May 2023
  • Duration 24 months
  • Mode of study Online, Part-time

Overview

Big Data skills are in high demand and they attract high salaries. If you want to become a data scientist, this is the course for you. The MSc Big Data at the University of Stirling is a taught advanced Master's degree covering coding skills, the technology of Big Data and the science of data analytics.

The syllabus includes:

  • Mathematics and Statistics for Big Data
  • Python scripting
  • Business and scientific applications of Big Data
  • Big databases and NoSQL including MongoDB, Cassandra and Neo4J
  • Analytics, machine learning and data visualisation using Python, Orange and ScikitLearn
  • Cluster computing with Hadoop, Spark, Hive and MapReduce
  • Student projects including possible internships with companies or technology providers
 

This is a 100% online course which gives you the opportunity to study in a way that suits your personal and professional needs. A combination of video lectures, live sessions and online materials are used to teach this course enabling you to access them whenever is the right time for you.

Scotland is a growing and dynamic country with an exciting future at the heart of the data science revolution. £661 million invested in vision of turning capital city into the ‘Data Capital of Europe’ (Source: Scottish Development International).

 

Top reasons to study with us

Course objectives

On successful completion of this programme, you should be able to demonstrate:

  1. an understanding of the issues of scalability of databases, data analysis, and search
  2. the ability to choose the right solution for a commercial task involving big data, including databases, architectures and cloud services
  3. an understanding of the analysis of big data including methods to visualise and automatically learn from vast quantities of data
  4. the programming skills to build simple solutions using big data technologies such as MapReduce and scripting for NoSQL, and the ability to write parallel algorithms for multi-processor execution

Professional accreditation

Free Microsoft Azure accreditation

Students on this programme are offered the opportunity to take Microsoft accredited courses in addition to their academic study. The additional courses are free and include access to the Microsoft Azure platform and the course exam. This year we offered Azure AI Fundamentals. The courses take one week and are taught by university lecturers. Students who pass the course receive Microsoft accreditation, which is highly sought after in the job market.

Work placements

There are opportunities for students to carry out their three month summer dissertation project as a placement with a company or technology provider. Students who are currently in work are supported in finding a project with their current employer if they wish to do so.

Flexible learning

If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.

Research overview

Our team of academics in the department of Computing Science and Mathematics investigate novel and effective approaches to dynamic and uncertain real-world problems in complex systems and environments. They explore the interdisciplinary connections between computer science, mathematics, life sciences, social sciences and management.

We work collaboratively with a number of organisations, including The Data Lab (Scotland’s Data Science Innovation Centre, which supports students with funding, networking and routes to employment) and the Scottish Informatics and Computing Science Alliance (SICSA), to ensure our students have the best platform to succeed.

Entry requirements

Academic requirements

A minimum of a second class Honours degree or equivalent in a numerate subject such as maths, computing, engineering or an analytic science. Applicants without these formal qualifications but with significant appropriate work experience are encouraged to apply.

If you don’t currently meet the academic requirements for this course, INTO University of Stirling offers a variety of preparation programmes that can earn you the qualifications and skills you need for direct entry.

Explore INTO Stirling programmes to see the pathway and pre-masters routes available for this course and others at the University of Stirling.

English language requirements

Due to disruption in English Language testing caused by COVID-19, we are accepting alternative English Language tests (including online English Language Tests).

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:

  • IELTS Indicator 6.0 with a minimum of 5.5 in each sub-skill 
  • Cambridge C1 Advanced (CAE) 169 overall with a minimum of 162 in each sub-skill
  • Cambridge C2 Proficiency (CPE) 180 overall with a minimum of 162 in each sub-skill
  • Pearson Test of English (Academic) 60 overall with a minimum of 59 in each sub-skill
  • IBT TOEFL 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing
  • IBT TOEFL Special Home Edition Test 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing
  • Trinity ISE II Pass overall with a Pass in each sub-skill, ISE III Pass overall and in all sub-skills, ISE IV Pass overall and in all sub-skills
  • Aptis (4 skills) CEFR B2 overall and B2 in all sub-skills
  • Duolingo 95 overall with a minimum of 90 in all sub-skills
  • LanguageCert International ESOL B2 Communicator -  Pass with minimum 33 in each sub-skill

Last updated: 1 February 2021

If you are from India, Ghana or Nigeria please also check your country/region specific page for any additional, or changes to, English language requirements.

For more information on ways that you can meet our English language requirements, including options to waive the requirement, please read our information on English language requirements.

Course details

Students studying on this course will be introduced Big Data concepts such as following.

Representing and Manipulating Data

This course provides an introduction to coding in Python and then covers the important data manipulation packages such as Numpy, Pandas, NLTK, OpenCV and Seaborn.

Mathematical Foundations

This course provides the basic mathematical tools required by any data scientist. It covers basic linear algebra, probability and set theory.

Statistics With R

This course provides students an introduction to statistics using the programming language, R. Students will learn basic statistical methods used to analyse quantitative data.

Relational and Non-Relational Databases

This course takes you through relational database design and SQL programming and the various NoSQL databases, including document stores like MongoDB, column stores like Cassandra and graph databases such as Neo4j. You'll learn to pick the right database for your application and how to build, search and distribute data in a commercial system.

Personal and Professional Development

The Personal and Professional Development (PPD) module on the Programme is designed to facilitate your self-awareness, communication, critical thinking, and team-working competences that are vital to becoming an effective and resilient manager within the field of Data Science. 

Data Analytics

You'll learn the practicalities of big data analytics with techniques from data mining, machine learning, statistics, and data visualisation. You’ll explore how we’re training computers to understand the present and predict the future with data from finance, marketing and social media. You will learn how to apply machine learning in a commercial setting and study the social and ethical considerations when doing so.

Cluster Computing

This course covers distributed data processing on cloud computing systems with Hadoop and MapReduce.

Scientific and Commercial Applications

With guest lectures from science and industry, this course presents a set of case studies of Big Data in action. You'll learn first-hand how companies are using big data in fields such as banking, travel, telecoms, genetics and neuroscience.

Modules

The module information below is intended only as an example of what you may study and features details for the current academic year (2021/22). Modules are regularly reviewed and are subject to future changes.

Course Details

You’ll learn through a combination of video lectures, live webinars and course materials that are easy to access wherever you are, whenever it works for you. Our intuitive learning hub also offers collaborative tools that make it easy to connect with tutors and fellow students, creating a rich online environment built around human-centred learning. You'll also have access to an extensive database of eBooks and journals, and free software such as Office 365.

You’ll carry out a project using a Big Data technology of your choice. With support from our staff, you’ll choose a specialist topic and become a real expert. You'll start with an in-depth analysis of the topic and its technology. Then you'll build a solution that will showcase your skills to employers and give you the knowledge to win a high level, high salary job.

The course uses a variety of assessment methods ranging from individual assignments, group assignments, business reports, online class tests, examinations, individual and group presentations and research design. Assignments will vary from module to module, with several technical assignments, some essay writing and some presentations.

Fees and funding

Fees and costs

Tuition fees
 2021/22 fee2022/23 fee
Total MSc course fee

£9,500

£9,975

This course is only offered on a part-time basis. The total course fee will be split over the years that you study. The total fee will remain the same and will be held at the rate it was set in your year of entry.

If you need to extend your period of study or repeat study, you will be liable for additional fees.

For more information on courses invoiced on an annual fee basis, please read our tuition fees policy.

Additional costs

There are some instances where additional fees may apply. Depending on your chosen course, you may need to pay additional costs, for example for field trips. Learn more about additional fees.

Scholarships and funding

Postgraduate Tuition Fee Loan

This course is currently approved for Postgraduate Tuition Fee Loan funding from the Student Awards Agency Scotland.

Payment options

We aim to be as flexible as possible, and offer a wide range of payment methods - including the option to pay fees by instalments. Learn more about how to pay

After you graduate

Big data skills are in high demand. You will have opportunities with data-driven companies from a wide variety of sectors and command a salary that’s typically higher than the IT average. Students graduating from this programme have found jobs everywhere from global companies to small startups. Here are a few of the sectors where our graduates now work:

  • Banking and Finance
  • Marketing
  • Data Consultancy
  • Healthcare
  • Sport
  • Education

Our Masters in Big Data has been developed in partnership with companies that employ data scientists and includes the possibility of an internship that will enable you to make industry connections that could benefit your future career.

We’re part of the DataLab MSc, which supports our students with funding, networking and routes into employment.

What our students said

Suprith Kumar
Suprith Kumar
MSc Big Data
Studying MSc Big Data at Stirling helped me learn more on advanced technologies, research works, new opportunities in the field of data science, and interpersonal skills. As part of the course, I did a placement with the Epidemiology Research Unit (FISH VET GROUP) as a Data Scientist Intern.
Read Suprith's story
Beth Watson
Beth Watson
MSc Big Data
The Big Data course was very well designed. The range of topics and technologies covered meant that students gained a basic knowledge in a variety of areas which can be further expanded in a future career.
Read Beth's story
Jinmo Yang
Jinmo Yang
Korea, South
MSc Big Data
What firstly attracted me to study Big Data at Stirling was the well-structured nature of the course. I like that I can get a general and practical understanding of the Big Data field.
Read Jinmo's story

Changes at Stirling

Find out about important changes including how you'll be taught, start dates and how we're making campus safer.

Which course would you like to apply for?

MSc Big Data (Online)

Search for another course