MSc
Data Science
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Why study MSc Data Science at Goldsmiths
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 MSc Data Science will prepare you to join a new generation of data scientists that are highly in demand across multiple industries.
- You’ll learn to combine the statistical skills of data analysis and the computational techniques needed to carry out this analysis on a large scale.
- You’ll learn the mathematical foundations of statistics, data mining and machine learning, and apply these to practical, real-world data.
- We’ll equip you with the computational techniques needed to efficiently analyse very large data sets.
- With guidance from industry experts, you’ll put your skills to the test using real-world data to analyse trends in social media, make financial predictions, and extract musical information from audio files.
- You’ll carry out original analysis on real-world data through your final project, which allows you to focus on your specific research interests.
- You’ll use industry-standard software such as Apache Hadoop and Spark to analyse data from industries such as biomedical, financial and social media.
- We have close links with leading industry professionals, who regularly deliver lectures and talks on Data Science.
- You’ll learn from experts in the Department of Computing and the Institute of Management Studies. Many faculty members bring their knowledge from active research and consultancy in a wide range of sectors.
Contact the department
If you have specific questions about the degree, contact Dr V L Raju Chinthalapati or Alan Zucconi.
Length
1 year full-time, 2-3 years part-time
Entry requirements
An undergraduate degree at 2:1 level or above in a subject such as computer science, mathematics, statistics, engineering, or quantitative subjects like economics and finance. You will require a level of mathematical dexterity that is commensurate with having completed a numerate degree.
Fees
Home - full-time: £12520
Home - part-time: £6260
International - full-time: £20460
Department
What you'll study
You will study the following modules:
Module title | Credits |
---|---|
Data Programming | 15 credits |
Machine Learning | 15 credits |
Big Data Analysis | 15 credits |
Statistics and Statistical Data Mining | 15 credits |
Data Science Research Topics | 15 credits |
Final Project in Data Science | 60 credits |
Note about optional modules (if available): The above is indicative of the typical modules offered, but is not intended to be construed or relied on as a definitive list of what might be available in any given year. The module content and availability is subject to change.
Teaching and assessment
Taught sessions and lectures provide overviews of themes, which you are encouraged to complement with intensive reading for presentation and discussion with your peers at seminars. Assessments build on lectures and seminars so you are expected to attend all taught sessions to build your knowledge and understanding of your chosen discipline.
All assessed work is accompanied by some form of feedback to ensure that your work is on the right track. It may come in a variety of forms ranging from written comments on a marked essay to oral and written feedback on developing projects and practice as they attend workshops.
Artificial Intelligence pathway
As well as MSc Data Science, we have the following pathway option in Artificial Intelligence:
In addition to pathway-specific skills in AI, you’ll learn core skills that are essential for data scientists such as statistical analysis, programming, machine learning, data visualisation, and big data technologies.
In collaboration with Goldsmiths Institute of Management Studies, you’ll learn the skills to become the next generation of data science experts.
Entry requirements
You'll gain a strong foundation in data science and specialist knowledge in a particular field. We do not assume that you will have programmed before, but we do require a level of mathematical dexterity that is commensurate with having completed a numerate degree. You'll have a BA or BSc Degree at 2.1 level or above in a subject such as computer science, mathematics, statistics, engineering, or quantitative subjects like economics and finance.
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 overall 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.
How to apply
Apply directly to Goldsmiths using our online application system
Before submitting your application you’ll need to have:
- Details of your academic qualifications
- The email address of your referee who we can request a reference from, or alternatively a copy of your academic reference
- Copies of your educational transcripts or certificates
- A 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.
Fees and funding
Annual tuition fees
These are the PG fees for students starting their programme in the 2024/2025 academic year.
- Home - full-time: £12520
- Home - part-time: £6260
- International - full-time: £20460
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 under a student visa. 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.
Funding opportunities
MSc Data Science Pathways Scholarships - We offer a number of partial tuition fee waivers for new full-time MSc Data Science students.
Explore the Goldsmiths scholarships finder to find out what other funding you may be eligible for.
Paying your fees
Find out about paying your tuition fees.
If you are a UK student you may be eligible for a postgraduate loan.
Meanwhile our Careers Service can also offer advice on finding work during your studies.
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.
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
We have a large and up-to-date collection of resources on the topic available to borrow from Goldsmiths' Library.
Career paths
Where your degree can take you
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.
Knowledge and skills
We carefully designed our MSc Data Science programme to help you to become successful data science professionals. Core modules provide you with a solid grounding in the theory of big data, statistics, machine learning. You’ll learn the latest methods and techniques to become an important member of different organisations as a data scientist and engineer.
You’ll get hands-on experience of data science through lab sessions, learning skills to take with you into your career.
With modules covering both fundamentals and current trends in data science, you’ll graduate with sought-after skills in the workplace. You’ll learn from a faculty of data science experts, guided by our Industry Advisory Board to make sure that teaching is relevant and up to date.
Once you graduate, you’ll have the skills to take up a wide variety of roles across many organisations and sectors.