Royal Holloway, University of London

Course Introduction

This course develops the practical skills needed to handle and analyse data in a wide variety of fields, preparing you for a rewarding career in Big Data. You?ll study in a department with a strong reputation for research excellence. This flexible programme gives you the chance to tailor your learning to your own strengths and interests, with a broad range of optional modules including Online Machine Learning, Methods of Bioinformatics and Microeconometrics providing scope and variety. You?ll be well-equipped to continue your studies at PhD level, which will place you in a strong position to pursue more advanced, research-based roles after graduation.

Skills that you will acquire include the ability to: work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, and neural networks; work with structured, unstructured, and time-series data; work with software packages such as MATLAB and R; design data processing solutions for data-intensive analytics problems; work with modern tools for massively distributed data processing, such as Hadoop and Pig, and Cloud Computing tools such as Amazon S3, EC2 and Elastic MapReduce; design Extract-Transfer-Load (ETL) pipelines; design Data Warehousing and Decision Support System (DSS) solutions; work with highly-scalable data-storage solutions, such as MongoDB, Cassandra, HBase, and other NoSQL Data Stores; work with data-intensive computing technologies, such as Hadoop MapReduce, Spark, Hive, and Pig; work with Cloud Computing tools, such as Amazon S3, EC2 and Elastic MapReduce.

We bring several companies to our campus throughout the year, both for fairs and for delivering advanced topics seminars, which are an excellent opportunity to learn about what they do and discuss possible placements or jobs. Our graduates enter into successful careers in academia or in companies or organisations operating in highly competitive areas. In recent years, these have included Amazon, American Express, BGL Group, Bupa, Capita, Centrica, EY, Facebook, Google, Hortonworks, JP Morgan, Microsoft, ONS, PWC, QuintilesIMS, Rolls Royce, Shell, UBS, VMware, Xerox and the Z/Yen Group.

Duration & Attendance Qualification Tuition fees Fee type
1 year
Full Time
MSc £11,300 Home Fees
1 year
Full Time
MSc £11,300 European Fees
1 year
Full Time
MSc £20,500 Overseas Fees
2 years
Part Time
MSc £5,650 Home Fees
2 years
Part Time
MSc £5,650 European Fees
2 years
Part Time
MSc £10,250 Overseas Fees

Qualifications required:

  • Domestic entry requirements: Students need to have a 2:1 in Computer Science, Economics, Mathematics, Physics, or other subjects that include a strong element of both mathematics and computing. Normally we require a UK 2:1 (Honours) or equivalent in relevant subjects but we will consider high 2:2 or relevant work experience. Candidates with professional qualifications in an associated area may be considered. Where a ?good 2:2? is considered, we would normally define this as reflecting a profile of 57% or above.
  • International entry requirements: Students will require: IELTS: 6.5 overall. No subscore lower than 5.5; Pearson Test of English: 61 overall. Writing 54. No subscore lower than 51; Trinity College London Integrated Skills in English (ISE): ISE III.