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 Python, 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. HSBC have a development centre in Stirling and have provided some very interesting Big Data projects to our students. Amazon’s development centre in Scotland is close by in Edinburgh.

The University of Stirling is a member of 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.

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.

Top reasons to study with us

#1 You’ll learn cutting-edge technologies, including Python, Hadoop, NoSQL and Machine Learning

#2 Our Data MSc is the largest and most successful of the Datalab programmes in Scotland

#3 Our graduates have an excellent reputation with employers for their skills and knowledge

Course objectives

The syllabus for the MSc Big Data 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 Weka, R and ScikitLearn
  • Cluster computing with Hadoop, Spark, Hive and MapReduce
  • Student projects including paid internships

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 long summer project, generally in partnership with a company or technology provider.

Course structure

Mathematics and Statistics for Big Data

  • Our foundation maths and computing courses ensure you have the theoretical grounding to build on for the rest of the course.
  • This module teaches basic linear algebra, probability theory and introductory statistics.

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.

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 and an exam, but the emphasis is on the coursework.

Course director

Dr Kevin Swingler

+44 (0) 1786 467676

kms@cs.stir.ac.uk

Fees - 2018/2019

  • Overseas £15,250
  • Home/EU £6,300
Program taught in:
English

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Last updated November 14, 2018
This course is Campus based
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Duration
12 - 24 months
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Price
6,300 GBP
Home/EU: £6,300 - Overseas: £15,250
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