MSc Big Data
Big Data skills are in high demand. Gain skills in big data technology, advanced analytics and industrial and scientific applications on our advanced Masters course.
Key facts
- Award Masters / MSc, Postgraduate Certificate, Postgraduate Diploma
- Start date September 2023, January 2024, September 2024, January 2025
- Duration September full-time 12 months; September part-time 24 months; January full-time 21 months
- Mode of study full time, part time
- Delivery on campus
Overview
Big data is increasingly important in today’s commercial landscape. As a data scientist specialising in big data, you’ll help companies make sense of large amounts of structured and unstructured data, providing rapid insights that enable them to make better, quicker decisions.
The MSc Big Data is a taught advanced Masters degree covering the technology of Big Data and the science of data analytics. You’ll gain practical skills in big data technology, advanced analytics and industrial and scientific applications.
The course will teach you how to collect, manage and analyse big, fast moving data for science or commerce. You’ll learn skills in cutting-edge technology such as Data Analytics, R, Hadoop, NoSQL and Machine Learning. At the same time, you’ll delve into important maths and computing theory, and learn the advanced computational techniques you need to develop your career in data science.
Our MSc has been developed in partnership with global and local companies who employ data scientists. Since the course was launched in 2012 we have developed a great relationship with employers who are looking for the skills that we teach.
The University of Stirling is associated with The Data Lab, an Innovation Centre that aims to develop the data science talent and skills required by industry in Scotland. It also supports our students with funding, networking and routes into employment. We also have close links with the Scottish Informatics and Computing Science Alliance (SICSA).
As a graduate in Big Data you’ll be able to work in a wide range of sectors such as digital technologies, energy and utilities, financial services, public sector and healthcare. The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in 2018 (Statista.com).
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, 2020).
Top reasons to study with us
Course objectives
The syllabus for the MSc Big Data includes:
- Mathematics and Statistics for Data Science
- Representing and Manipulating Data in Python
- Relational and Non Relational Databases
- Commercial and Scientific Applications
- Machine Learning
- Cluster Computing
- Dissertation Project of Your Choice
On this Masters course you’ll gain:
- an understanding of the issues of scalability of databases, data analysis, search and optimisation;
- the ability to choose the right solution for a commercial task involving big data, including databases, architectures and cloud services;
- an understanding of the analysis of big data including methods to visualise and automatically learn from vast quantities of data;
- the programming skills to build solutions using big data technologies such as MapReduce and scripting for NoSQL, and the ability to write parallel algorithms for multi-processor execution.
Work placements
The course features a substantial summer project, generally in partnership with a company or technology provider.
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. Applicants without these formal qualifications but with significant appropriate/relevant work/life experience are encouraged to apply.
Other routes of entry
If you don't currently meet our academic requirements, INTO University of Stirling offers a variety of preparation programmes that can earn you the qualifications and skills you need to progress onto some of our courses. Explore INTO University of Stirling to see the pathway and pre-masters routes available.
International entry requirements
English language requirements
If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS Academic or UKVI 6.0 with a minimum of 5.5 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.
See our information on English language requirements for more details on the language tests we accept and options to waive these requirements.
Pre-sessional English language courses
If you need to improve your English language skills before you enter this course, our partner INTO University of Stirling offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for entry to this degree.
Find out more about our pre-sessional English language courses.
Course details
Course structure
Mathematical Foundations
This course will equip students with some basic mathematical knowledge and problem-solving skills.
Statistics for Data Science
The course is intended to give students:
- a basis for the analysis and interpretation of quantitative information;
- an understanding of the basic ideas underlying statistical methods at an introductory level;
- an understanding of how to overcome problems when analysing big data sets.
Relational and Non-Relational Databases
- After covering relational databases and SQL, this course takes you through 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 the data in them.
Machine Learning
- 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’ll learn how to apply machine learning techniques such as neural networks and decision trees to practical problems.
Cluster Computing
- This course covers distributed data processing with Hadoop and MapReduce in addition to the use of Condor for distributed computation.
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.
For students interested in a January start, the duration of the course will be 21 months. For example, students starting in January 2023 will graduate in November 2024. This decision was made to allow students to learn flexibly and enhance other skills during the summer months when teaching is not available.
Modules
The module information below provides an example of the types of course module you may study. The details listed are for the current academic year (September 2023). Modules and start dates are regularly reviewed and may be subject to change in future years.
Course Details
Teaching
There’s a real mix of practical technology sessions taught in labs and workshops along with lectures, seminars and tutorials teaching you the Big Data theories.
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.
We have a programme of invited speakers from industry giving you the opportunity to ask questions of people who are doing data science every day. Recent participants include MongoDB, SkyScanner and HSBC.
Assessment
This is a practical course and the assessment reflects that. Each module has an assignment or an exam or both, but the emphasis is on the course work.
Course director
Fees and funding
Fees and costs
| 2023/24 | 2024/25 | |
|---|---|---|
| Students from the UK and Republic of Ireland | £10,350 | £10,900 |
| International (including EU) students | £21,845 | £22,900 |
University of Stirling alumni will automatically be awarded a fee waiver for the first year of Masters studies through our UK/Republic of Ireland Alumni Scholarship.
Applicants from the UK or Republic of Ireland who hold a first-class honours degree or equivalent will automatically be awarded a £2,000 scholarship through our Postgraduate Merit Scholarship.
Fees shown are for a full-time, one-year Masters course.
If you need to extend your period of study, you may be liable for additional fees.
If you are studying part time, 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 set in your year of entry.
For more information on courses invoiced on an annual fee basis, please read our tuition fee policy.
Eligible students could receive a scholarship worth between £4,000-£7,000. See our range of generous scholarships for international postgraduate students.
Fees shown are for a full-time, one-year Masters course.
If you need to extend your period of study, you may be liable for additional fees.
If you are studying part time, 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 set in your year of entry.
For more information on courses invoiced on an annual fee basis, please read our tuition fee policy.
Postgraduate tuition fee loans
This course is eligible for a postgraduate tuition fee loan from one of the UK’s governments. See the Scholarships and funding section, below, for more details.
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
Funding
Eligible international students could receive a scholarship worth between £4,000-£7,000. See our range of generous scholarships for international postgraduate students.
University of Stirling alumni will automatically be awarded a fee waiver for the first year of Masters studies through our UK/Republic of Ireland Alumni Scholarship or International Alumni Scholarship.
Applicants from the UK or Republic of Ireland who hold a first-class honours degree or equivalent will automatically be awarded a £2,000 scholarship through our Postgraduate Merit Scholarship.
If you have the talent, ability and drive to study with us, we want to make sure you make the most of the opportunity – regardless of your financial circumstances.
Learn more about available funding opportunities or use our scholarship finder to explore our range of scholarships.
Postgraduate tuition fee loans
Scottish students may be eligible to apply to the Students Award Agency for Scotland (SAAS) for loans of up to £11,500 to cover tuition fees and associated living costs.
English students can apply for a loan of up to £12,167 each year as part of the Postgraduate Masters Loan Scheme.
Welsh students can apply for financial support of up to £18,770 as a combination of grant and loan from Student Finance Wales.
Northern Irish students can apply for a postgraduate tuition fee loan of up to £5,500 from Student Finance NI.
Cost of living
If you’re domiciled in the UK, you can typically apply to your relevant funding body for help with living costs. This usually takes the form of student loans, grants or bursaries, and the amount awarded depends upon your personal circumstances and household income.
International (including EU) students won’t normally be able to claim living support through SAAS or other UK public funding bodies. You should contact the relevant authority in your country to find out if you’re eligible to receive support.
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. As a graduate in Big Data you’ll be able to work in a wide range of sectors, such as digital technologies, energy and utilities, financial services, public sector and healthcare.
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 are also part of The Data Lab which supports students with funding, networking and routes into employment.
Big Data professionals earn an average 31% more than other IT professionals in the industry.
What our students said
MSc Big Data
Read Suprith's storyStudying 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.
MSc Big Data
Read Beth's storyThe 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.
South Korea
MSc Big Data
Read Jinmo's storyWhat 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.