MSc Big Data

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

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

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.

• 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.