MSc Big Data
University of Stirling
Key Information
Campus location
Stirling, United Kingdom
Languages
English
Study format
On-Campus
Duration
12 - 24 months
Pace
Full time, Part time
Tuition fees
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Application deadline
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Earliest start date
Sep 2024
* For up to date fee information, please see website
Introduction
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.
Top reasons to study with us
#1 You’ll learn cutting-edge technologies, including Data Analytics, 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
Curriculum
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.
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
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.
Please note that for those 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.
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.
Gallery
Career Opportunities
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.