About the course
The importance of Big Data grows year on year, with sectors including healthcare, manufacture, retail, administration and more reliant on the insights that accurate data capture and analysis can provide. Study Data Science and Analytics at Royal Holloway, University of London and you’ll develop 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. The Department of Computer Science was ranked 11th in the UK for the quality of its research publications (Research Excellence Framework 2014), and you’ll have the opportunity to contribute to this leading research culture with your own Individual Project.
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.
Follow your passion for Data Science and Analytics at Royal Holloway and you’ll graduate with a desirable Masters degree from a highly regarded department, as well as transferable skillset that’s both in short supply and in high demand by employers. Our location near the M4 corridor – also known as ‘England’s Silicon Valley’ – means students can benefit from networking and placement opportunities with some of the country’s top technology institutions.
- Study in a highly-regarded department, ranked 11th in the UK for research publications (Research Excellence Framework 2014).
- Benefit from strong industry ties, with close proximity to ‘England’s Silicon Valley’.
- Graduate with a Masters degree leading to excellent graduate employability prospects.
- Tailor your learning with a wide range of engaging optional modules.
- Choose from a one-year programme structure or add an optional year in industry.
- Data Analysis
- Computation with Data
- Programming for Data Analysis
- Database Systems
- Large-Scale Data Storage and Processing.
- Individual Project
In addition to these mandatory course units there are a number of optional course units available during your degree studies. The following is a selection of optional course units that are likely to be available. Please note that although the College will keep changes to a minimum, new units may be offered or existing units may be withdrawn, for example, in response to a change in staff. Applicants will be informed if any significant changes need to be made.
- Machine Learning
- Methods of Computational Finance
- Software Verification
- Advanced Data Communications
- Fundamentals of Digital Sound and Music
- Intelligent Agents and Multi-Agent Systems
- Semantic Web
- Internet and Web Technologies
- On-line Machine Learning
- Service-Oriented Computing, Technology and Management
- Business Intelligence Systems, Infrastructures and Technologies
- Computational Optimisation
- Methods of Bioinformatics
- Visualisation and Exploratory Analysis
- Financial Econometrics
- Investment and Portfolio Management
- Fixed Income Securities and Derivatives
- Decision Theory and Behaviour
- The Economics of Banking
- Private Equity
- Applied Probability
- Security Technologies
- Introduction to Cryptography and Security Mechanisms
- Network Security
- Computer Security (Operating Systems)
- Security Management
- Smart Cards, RFIDs and Embedded Systems Security
- Digital Forensics
- Security Testing - Theory and Practice
- Software Security
- Database Security
- Cyber Security
Teaching & assessment
Teaching is organized in terms of 11 weeks each. Examinations are taken in April / May of each academic year, except for Data Analysis for which the exam is in January. The individual project is taken over 12 weeks during the Summer.
A weekly seminar series runs in parallel with the academic programme, which includes talks by professionals in a variety of application areas as well as workshops that will train you to find a placement or a job and lead a successful career.
Assessment is carried out by a variety of methods including coursework, small group projects, and examinations, the proportions of which vary according to the nature of the modules.
This degree can be taken part-time.
Your future career
Study Data Science and Analytics at Royal Holloway, University of London and you'll graduate with excellent employability prospects in a range of fields.
You’ll develop a range of highly sought-after transferable skills, while our proximity to the M4 corridor technology hub – also known as ‘England’s Silicon Valley’ – will provide you with excellent placement and networking opportunities to pave the way for a rewarding future career. Our recent graduates have gone on to enjoy roles at organisations such as British Aerospace, Microsoft, Amazon, American Express and many more.
- 90% of Royal Holloway graduates in work or further education within six months of graduating.
- Strong industry ties help to provide placement and networking opportunities with some of the country’s leading institutions.
- On-site College Careers Service provides help and support for students.