MSc Big Data

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Tuition fee
Apply by
Start date
Jan 2025
Sep 2025
Sep 2026
Duration
Campus
Mode of study
Fees and deadlines depend on the selected options. Fees and currency conversion are approximate.
Offer response
1 weeks after your application is submitted
Backlogs accepted
This course accepts backlogs

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. Since the course was launched in 2012 we have developed a great relationship with employers who are looking for the skills that we teach. Students can also exit with PGCert and PGDip awards.

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 the possibility of paid internships
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Requirements

The requirements may vary based on your selected study options.





















Modules

  • Representing and Manipulating Data (ITNPBD2)
  • Mathematical Foundations (ITNPBD1)
  • Networks & Graph Theory (MATPMD2)
  • Commercial and Scientific Applications (ITNPBD4)
  • Statistics for Data Science (MATPMD1) Machine Learning (ITNPBD6)
  • Cluster Computing (ITNPBD7)
  • Relational and non-Relational Databases (ITNPBD3)
  • Dissertation Project (ITNPBD5)
  • Research Dissertation Project (ITNPMR9)
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    Use our magical AI system, to check your admission chances for this course.
    Tuition fee
    Apply by
    Start date
    Jan 2025
    Sep 2025
    Sep 2026
    Duration
    Campus
    Mode of study
    Fees and deadlines depend on the selected options. Fees and currency conversion are approximate.
    Offer response
    1 weeks after your application is submitted
    Backlogs accepted
    This course accepts backlogs