The MSc Data Science will provide you with the technical and practical skills to analyse the big data that is the key to success in future business, digital media and science.
The rate at which we are able to create data is rapidly accelerating. According to IBM, globally, we currently produce over 2.5 quintillion bytes of data a day. This ranges from biomedical data to social media activity and climate monitoring to retail transactions. These enormous quantities of data hold the keys to success across many domains from business and marketing to treating cancer or mitigating climate change.
The pace at which we produce data is rapidly outstripping our ability to analyse and use it. Science and industry are crying out for a new generation of data scientists who combine the statistical skills of data analysis and the computational skills needed to carry out this analysis on a vast scale.
The MSc Data Science provides you with these skills.
Studying this Masters, you will learn the mathematical foundations of statistics, data mining and machine learning, and apply these to practical, real world data.
As well as these statistical skills, you will learn the computational techniques needed to efficiently analyse very large data sets. You will apply these skills to a range of real world data, under the guidance of experts in that domain. You will analyse trends in social media, make financial predictions and extract musical information from audio files.
The degree will culminate in a final project in which you will you can apply your skills and follow your specialist interests. You will do a novel analysis of a real world data of your choice.
The programme includes:
- A firm grounding in the theory of data mining, statistics and machine learning
- Hands-on practical real world applications such as social media, biomedical data and financial data with Hadoop (used by Yahoo!, Facebook, Google, Twitter, LinkedIn, IBM, Amazon, and many others), R and other specialised software
- The opportunity to work with real-world software such as Apache
We have close links with industry and regularly invite leading professionals to deliver lectures and talks on Data Science.
Contact the department
If you have specific questions about the degree, contact the Programme Director, Dr Daniel Stamate
What you'll study
|Machine Learning and Statistical Data Mining||30 credits|
|Big Data Applications||15 credits|
|Data Programming||15 credits|
|Data Science Research Topics||15 credits|
|Final Project in Data Science||60 credits|
You will also choose from an anually approved list of modules which may include:
|Artificial Intelligence||15 credits|
|Interaction Design||15 credits|
|Neural Networks||15 credits|
|Data Visualisation and the Web||15 credits|
|Introduction to Natural Language Processing||15 credits|
|Geometric Data Analysis||15 credits|
Please note that due to staff research commitments not all of these modules may be available every year.
You should have an undergraduate degree of at least upper second class standard in computing, physics and engineering, mathematical sciences or finance, and an interest in and capability for working in interdisciplinary contexts.
In exceptional circumstances, outstanding practitioners or individuals with strong commercial experience may be considered.
We accept a wide range of international qualifications. Find out more about the qualifications we accept from around the world.
If English isn’t your first language, you will need an IELTS score (or equivalent English language qualification) of 6.5 with a 6.5 in writing and no element lower than 6.0 to study this programme. If you need assistance with your English language, we offer a range of courses that can help prepare you for postgraduate-level study.
Fees, funding & scholarships
Annual tuition fees
These are the fees for students starting their programme in the 2019/20 academic year.
- Home/EU - full-time: £10140
- Home/EU - part-time: £5070
- International - full-time: £15040
If you're an international student interested in studying part-time, please contact our Admissions Team to find out if you're eligible.
If you are looking to pay your fees please see our guide to making a payment.
In addition to your tuition fees, you'll be responsible for any additional costs associated with your course, such buying stationery and paying for photocopying. You can find out more about what you need to budget for on our study costs page.
There may also be specific additional costs associated with your programme. This can include things like paying for field trips or specialist materials for your assignments. Please check the programme specification for more information.
Find out more about postgraduate fees and explore funding opportunities. If you're applying for funding, you may be subject to an application deadline.
How to apply
You apply directly to Goldsmiths using our online application system.
Before submitting your application you'll need to have:
- Details of your education history, and, if available, an electronic copy of your educational transcript (this is particularly important if you have studied outside the UK, but isn't mandatory)
- The email address of your referee who we can request a reference from, or alternatively an electronic copy of your academic reference
- A personal statement – this can either be uploaded as a Word Document or PDF, or completed online
You'll be able to save your progress at any point and return to your application by logging in using your username/email and password.
When to apply
We accept applications from October for students wanting to start the following September.
We encourage you to complete your application as early as possible, even if you haven't finished your current programme of study. It's very common to be offered a place conditional on you achieving a particular qualification.
If you're applying for external funding from one of the Research Councils, make sure you submit your application by the deadline they've specified.
Late applications will only be considered if there are spaces available.
Admission to many programmes is by interview, unless you live outside the UK. Occasionally, we'll make candidates an offer of a place on the basis of their application and qualifications alone.
Find out more about applying.
Facilities include a Big Data Management & Analytics dedicated cluster of servers based on some of the most recent Xeon processors and fast RAM, and lab workstations, providing access to software platforms and languages specialised in Machine Learning, Data Mining, Statistical Analysis, and Big Data including:
- IBM SPSS
- Apache Hadoop ecosystem
- NoSQL databases as MongoDB
- Apache Spark
- Apache Storm
Our facilities also include a large and up to date collection of books on the topic (a sample of which is illustrated here) available to borrow from Goldsmiths' Library. You can look under the Data Mining module to find out more about this.
Data Science is one of the fastest growing sectors of employment internationally. Big Data is an important part of modern finance, retail, marketing, science, social science, medicine and government.
The study of a combination of long established fields such as statistics, data mining, machine learning and databases with very modern and strongly related fields as big data management and analytics, sentiment analysis and social web mining, offers graduates an excellent opportunity for getting valuable skills in advanced data processing.
This could lead to a variety of potential jobs including:
- Data Scientist
- Data Mining Analyst
- Big Data Analyst
- Hadoop Developer
- NoSQL Database Developer
- R Programmer
- Python Programmer
- Researcher in Data Science and Data Mining
Find out more about employability at Goldsmiths.