Universities United Kingdom University of Stirling Courses MSc Big Data

MSc Big Data
at University of Stirling

Stirling, United Kingdom

Tuition Fee £ 21,345
Country Rank#52
Duration12 Months
Score IELTS: 6 TOEFL: 78

Program 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.

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).

Course Content
Course structure

Mathematical Foundations

This course will equip student with the 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
Big Databases
- After a recap of 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.
Big Data Analytics
- You'll learn the practicalities of big data analytics with techniques from data mining, machine learning, statistics, data visualisation and web analytics. You’ll explore how we’re training computers to understand the present and predict the future with data from finance, marketing and social media.
Analytical and problem solving methods you will learn include:
- Maths and Statistics
  
  Probability and likelihood
  
  Information theory
  
  Linear algebra
  
  Statistics
- Data Mining
  
  Neural networks
  
  Bayesian networks
  
  Decision Trees
  
  DM project management
Hadoop and MapReduce
- 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.
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 2021). Modules and start dates are regularly reviewed and may be subject to change in future years.

Year 1, Autumn semester

Compulsory module
- Representing and Manipulating Data (ITNPBD2) 20 credits
Compulsory module

Select 10 credits from MSc Big Data Autumn Options list
- Mathematical Foundations (ITNPBD1) 10 credits
- Networks & Graph Theory (MATPMD2) 10 credits
Compulsory module
- Commercial and Scientific Applications (ITNPBD4) 20 credits
Compulsory module
- Statistics for Data Science (MATPMD1) 10 credits
Year 1, Spring semester

Compulsory module
- Machine Learning (ITNPBD6) 20 credits
Compulsory module
- Cluster Computing (ITNPBD7) 20 credits
Compulsory module
- Relational and non-Relational Databases (ITNPBD3) 20 credits
Year 1, Summer semester

Dissertation

Select 60 credits from Big Data Dissertation Options list
- Dissertation Project (ITNPBD5) 60 credits
- Research Dissertation Project (ITNPMR9) 60 credits
Entry Requirement
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 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.

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
- 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 - High Pass overall with minimum 25 in each sub-skill
Fees & Scholarships
Overseas (non-EU) students

2022/23 - £21,345
2023/24 - £21,845

Course fees

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.
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.

European Union and overseas 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.
Career Prospect
- 95% of our postgraduate leavers are in employment or further study within fifteen months of graduating (Graduate Outcomes Survey 2021, HESA)
- Our career services is 1st in Scotland, top 5 in the UK and top 15 in the world (UK International Student Barometer (ISB) Benchmark and Global ISB Benchmark 2018)
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.

Cost Of Studying At University of Stirling

Interest rates as low as 8.9% ^*

250K+

Students Assisted

800Cr+

Loan Amount Disbursed

5000+

Loans Sanctioned

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MSc Big Data at University of Stirling