Course information




1 year full-time; 2 years part-time; distance learning

Course overview

Goldsmiths works in partnership with the University of London Worldwide on a distance learning version of this programme. Find out more on the University of London course page

We will be making some changes to the way our programmes will be delivered in 2021-22 to ensure we continue to respond to the ongoing Covid-19 pandemic. All programmes will be delivered in-person on campus with some specific sessions within each programme being delivered online in a pre-recorded format. Where necessary, changes will also be made to assessment formats.

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 can apply your skills and follow your specialist interests. You will do a novel analysis of 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 Dr Larisa Soldatova.

What you'll study

You will study the following compulsory modules.
Compulsory modules Module title Credits
  Machine Learning 15 credits
  Big Data Applications 15 credits
  Data Programming 15 credits
  Data Science Research Topics 15 credits
  Final Project in Data Science 60 credits
  Statistics and Statistical Data Mining 15 credits

You will also choose 45 credits of option modules from an annually approved list of modules which may include the following.

Option modules Module title Credits
  Artificial Intelligence 15 credits
  Interaction Design 15 credits
  Neural Networks 15 credits
  R Programming 15 credits
  Data Visualisation and the Web 15 credits
  Introduction to Natural Language Processing 15 credits
  Geometric Data Analysis 15 credits

Download the programme specification. If you would like an earlier version of the programme specification, please contact the Quality Office.

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

For 2021-22 and 2020–21, we have made some changes to how the teaching and assessment of certain programmes are delivered. To check what changes affect this programme, please visit the programme changes page.

What our students say


"The leadership of this programme was amazing – probably the best supervision and mentorship throughout my higher education period."

"I studied Data Science at Goldsmiths from 2016 to 2017. Actually, I jumped into the MSc in Data Science from my PhD programme in Social Sciences. The reason for this switch was the increasing importance of data science in all walks of life and sectors. I have since been offered a job at a renowned, world-class university in London.

The programme has been an amazing learning process. I have learnt as much in one year as in ten years of social sciences. The leadership of this programme was amazing as well – probably the best supervision and mentorship throughout my higher education period. Additionally, the syllabus was created in such a way that any lay person will get the chance to learn Machine Learning, coding, Natural Language Processing and Big Data. It is indeed a valuable program, with so much mentorship alongside as well as many project opportunities.

One of the projects I have been involved in, with the Data Science laboratory the department owns, was in the health sector. Specifically, using Machine Learning in predicting the time of remission in psychotic patients. It was a valuable and meaningful experience that lead to other opportunities, such as working in the health sector as a research assistant in Data Science, at Imperial College."


The teaching staff is very friendly and expert in respective fields. They are always eager to help if required.

"I did my master’s in software engineering in Bangladesh. I always wanted to study in abroad so that I get to know about different cultures, regions, food, and people. I chose this program because of the course content. It is well organized and connected with real-life experiences. Moreover, recieveing the commonwealth shared scholarship helped me pursue my dream.

I have now been here for two months. The atmosphere of the university is very welcoming. The first thing that grabbed my attention was the university campus. It is large, lively and beautiful. The teaching quality is excellent. The teaching staffs are very friendly and expert in respective fields. They are always eager to help if required. Other staff are also helpful. The university offers a great range of facilities from education (well-equipped lab, rich library) to recreation. There are several organizations connected to university, like the students union and CEN8 which offer students different types of activities. I am involved with some of these organizations which helped me to meet with people from diverse backgrounds. During my time at Goldsmiths, I expect to expand my professional network, do some quality research in my field, and enjoy my surroundings. London is an amazing city full of history. I feel fortunate to be here. It is one of the best decisions that I have made."


"The high quality of tuition and care for students coupled with extracurricular activities proposed by Dr Stamate, as part of the MSc Data Science, have significantly helped my success in securing my ‘dream job’."

"The MSc Data Science (on-campus programme) lead by Dr Daniel Stamate is the right balance between theory and practice, across all modules I studied. The strong point of the MSc Data Science is that students can choose the subject for their coursework, for example, finance, medical studies, transport, etc. as long as expectations set with each lecturer are met. This enables each student to directly apply the Data Science/AI/Big Data skills to real-world problems of their interests.

It then gives the opportunity for students to build their portfolio of use cases, that can then be demonstrated during interviews.

Dr Daniel Stamate also provides the opportunity for proactive students to benefit from the ‘Data Science and Soft Computing Lab’ where students can further their knowledge, practice with real data and potentially meet with professionals from the industry. This was certainly the case in my experience and I am still in contact with some of these people to date.

I worked on many projects ranging from NLP, AI and Machine Learning domains. My major project was my MSc thesis which focused on analysing the predicting power of sentiment on the XLE index and XLE index’s constituents market trend and volatility.

On the big data side, I wrote a functional and performance comparison between two Hadoop components, namely Hive and Spark, in the context of analysing airport flights’ delays/cancellations.

On the AI side, I implemented and compared the performance of two informed search algorithms, namely the AStar and Jump First Point, based on numerous scenarios involving an agent moving in a 2D grid, containing ‘road blocks’.

I am now a Data Scientist working for a major commercial bank. As a summary, the high quality of tuition and care for students coupled with extracurricular activities proposed by Dr Stamate, as part of the MSc Data Science, have significantly helped my success in securing my ‘dream job’."

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.

International qualifications

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 2021/2022 academic year.

  • Home - full-time: £10870
  • Home - part-time: £5435
  • International - full-time: £17760

If your fees are not listed here, please check our postgraduate fees guidance or contact the Fees Office, who can also advise you about how to pay your fees.

It’s not currently possible for international students to study part-time if you require a Student Visa, however this is currently being reviewed and will be confirmed in the new year. Please read our visa guidance in the interim for more information. If you think you might be eligible to study part-time while being on another visa type, please contact our Admissions Team for more information.

If you are looking to pay your fees please see our guide to making a payment.

Additional costs

In addition to your tuition fees, you'll be responsible for any additional costs associated with your course, such as 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.

Funding opportunities

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
  • personal statement – this can either be uploaded as a Word Document or PDF, or completed online

          Please see our guidance on writing a postgraduate statement

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.


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
  • 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.


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.

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