Navigation

MSc in Data Science

  • Length
    1 year full-time or 2 years part-time
  • Department
    Computing

Course overview

The MSc in 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 in 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

Talks

We have close links with industry and regularly invite leading professionals to deliver lectures and talks on Data Science. 

Staff

 

Contact the department

If you have specific questions about the degree, contact the Programme Director, Dr Daniel Stamate

Modules & structure

You will study the following core modules:
Module title Credits
  Machine Learning & 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 the following optional modules:

Module title Credits
  Neural Networks 15 credits
  Geometric Data Analysis 15 credits
  Interactive Data Visualisation 15 credits
  Artificial Intelligence 15 credits
  Data Compression 15 credits
  Natural Language Processing 15 credits

Download the programme specification for this degree to find out more about what you'll learn and how you'll be taught and assessed.

Please note that due to staff research commitments not all of these modules may be available every year.

Department

Computing at Goldsmiths is ranked: 2nd in London for this subject area** 17th in the UK for the quality of our research***

Computing

The Department of Computing offers a creative, contemporary and pioneering approach to the discipline.

From developing computers that can compose music and paint pictures, to defining and implementing new social media tools and applications, we aim to invigorate computing and the world around it. 

Learn by doing

We place a great emphasis on creativity, independence and ‘learning by doing’. Students undertake practical work in real-world situations, carrying out projects in ways that mirror industry practice. 

Interdisciplinary approach

We also promote an interdisciplinary approach to the subject: from computational arts to games and entertainment, and from data science to digital journalism. 

Industry experts

You’ll be taught by industry experts – our academics are deeply engaged in current research, with many applying their knowledge and skills to developing cutting-edge technology. And we have close links with industry, too, regularly inviting leading professionals to deliver lectures and talks. 

Find out more about the Department of Computing.

**Guardian University League Tables 2017

***Research Excellence Framework 2014, Times Higher Education research intensity subject rankings

Facilities

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:

  • R
  • IBM SPSS
  • SAS
  • Python
  • Apache Hadoop ecosystem
  • NoSQL databases as MongoDB
  • Apache Spark
  • Apache Storm
  • RapidMiner
  • Tableau

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.

Skills & careers

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.

Entry requirements

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.

Equivalent qualifications
We accept a wide range of international qualifications. Find out more about the qualifications we accept from around the world.

English language requirements
If English isn’t your first language, you’ll need to meet our English language requirements to study with us.

For this programme we require:

IELTS 6.5 (with a minimum of 6.5 in the written test and no individual test lower than 6.0)

If you need assistance with your English language, we offer a range of courses that can help prepare you for postgraduate-level study.

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, including the dates of all exams/assessments
  • The email address of your referee who we can request a reference from, or alternatively an electronic copy of your academic reference
  • personal statement – this can either be uploaded as a Word Document or PDF, or completed online
  • If available, an electronic copy of your educational transcript (this is particularly important if you have studied outside of the UK, but isn’t mandatory)

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.

Selection process 

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.

Fees & funding

Find out more about funding opportunities for home/EU applicants, or funding for international applicants. If you're applying for funding, you may be subject to an application deadline.

The Department of Computing offers a number of scholarships for students with remarkably good applications. The scholarships will be a one-off payment of £2,000. You don't need to submit a separate application to be considered for one of these awards. You can find out more from the department.

Find out more about tuition fees.

Related content links