Why an MSc Big Data ?
Big data skills are in high demand and they attract high salaries. The MSc Big Data is a taught advanced Masters degree covering the technology of big data and the science of data analytics.
This course has been developed in partnership with global companies who employ data scientists. Over 90% of our students find work or further study within 6 months of finishing the course in diverse sectors such as banking and finance, health services, data science consultancy, data driven marketing, and even sports science. Big data will become increasingly important to the finance sector and relevant skills are in high demand.
The course features a summer project, where possible in partnership with a company or external organisation that provides students with a showcase of their skills to take to employers or launch online.
This big data masters course is a technical programme designed to give you the skills to work as a data scientist. We expect you will have an interest in computing and some ability to program.
You will need a numerate degree and, while we will cover the skills you need, you should be comfortable with mathematics and probability.
Big data skills are in high demand both from the new global giants such as Amazon, Apple and Google and in the fields of retail, marketing, finance, medicine and scientific research. These jobs are often in new and exciting cutting edge fields and are currently attracting high salaries. A recent Strata report found the average salary for analysts with the skills you will learn on this course was $130k.
Data Scientist: The Sexiest Job of the 21st Century
Harvard Business Review
Course structure and content :
The MSc Big Data is a mix of practical technology such as Hadoop, NoSQL, and Map-Reduce, important maths and computing theory, and advanced computational techniques. The course will teach you what you need to know to collect, manage and analyse big, fast moving data for science or commerce.
You’ll learn from lectures, practical labs and small tutorial groups during the first two semesters from September to April.
The course covers:
Course modules :
This course will equip student with the some basic mathematical knowledge and problem solving skills.
The course is intended to give students a basis for the analysis and interpretation of quantitative information; as well as an understanding of statistical methods at an introductory level and how to overcome problems when analysing big data sets.
After a recap of SQL, this course takes you through the various NoSQL databases such as document stores like MongoDB, column stores like Cassandra and graph databases like Neo4j. You’ll learn to pick the right database for your application and how to build, search and distribute the data in them.
Sometimes, the more data you have, the better hidden the important facts become.
Distilling information from big data needs fast, parallel analytics. We guide you through machine learning, data visualisation, web analytics and sentiment analysis. You’ll learn the practicalities of big data analytics with techniques from data mining, machine learning, statistics, data visualisation and web analytics. Learn how we are training computers to understand the present and predict the future with data from finance, marketing, and social media.
This course covers distributed data processing with Hadoop and MapReduce in addition to the use of Condor for distributed computation.
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.
Key Information :
Degree type: MSc
Study method: full-time (15 Months) or part-time (24 Months)
Start date: September Course length: 15 Months
Entry requirements :
A minimum of a second class honours degree (2.1 preferred) or equivalent in a relevant subject is required. Applicants without these formal qualifications but with significant relevant work experience are encouraged to apply. Degrees should be in a numerate subject such as maths, computing, engineering or an analytic science.
If English is not your first language, you must provide evidence of your proficiency such as a minimum IELTS score of 6.0 (5.5 in all bands).