Data Science BSc
Data Science BSc (2024)
This programme provides a comprehensive training in the statistical basis of data science, along with a solid grounding in the computing skills and algorithmic reasoning necessary for modern data analysis.
UK tuition fees (2024/25)
Overseas tuition fees (2024/25)
Programme startsSeptember 2025
Application deadline29 Jan 2025
UCAS course code
- A* in Mathematics required. Further Mathematics preferred. If you are studying both then the A* can be in either subject. Other preferred subjects include Chemistry, Economics, Physics and Statistics.
- English Language and Mathematics at grade C or 4.
Contextual offer information
Contextual offers are typically one to two grades lower than the standard offer. Grade and subject requirements for contextual offers for this programme will be published in Summer 2024.
- A total of 19 points in three higher level subjects including grade 7 in Mathematics, with no higher level score below 5. The programme will accept either 'Mathematics: Analysis and Approaches' or 'Mathematics: Applications and Interpretation' at higher level. Further Mathematics, Chemistry, Economics, Physics and Statistics preferred.
Contextual offers are typically one to two grade boundaries (equivalent to A levels) lower than the standard offer. IB Diploma grade and subject requirements for contextual offers for this programme will be published in Summer 2024.
UK applicants qualifications
For entry requirements with other UK qualifications accepted by UCL, choose your qualification from the list below:
Pass in Access to HE Diploma, with a minimum of 36 credits at Distinction and 9 credits at Merit, all from Level 3 units. Please note, where subject specific requirements are stipulated at A level we will review your Access to HE syllabus to ensure you meet the subject specific requirements prior to a final decision being communicated.
BTEC Level 3 National Extended Diploma (RQF - teaching from 2016) with Distinction, Distinction, Distinction to include Distinction in Engineering Principles and Calculus to Solve Engineering Problems.
D2,D3,D3 in three Cambridge Pre-U Principal Subjects. Mathematics at D2 required. Further Mathematics is preferred. If you are studying both subjects then D2 can be in either subject. Other preferred subjects include Chemistry, Economics, Physics and Statistics.
A1,A,A at Advanced Highers (or A1,A at Advanced Higher and A,A,A at Higher), including A1 in Mathematics at Advanced Higher. Further Mathematics, Chemistry, Economics, Physics and Statistics preferred.
Not acceptable for entrance to this programme.
Not acceptable for entrance to this programme.
Successful completion of the WBQ Advanced Skills Challenge Certificate plus 2 GCE A levels at grades A*AA, including A* in Mathematics. Further Mathematics is preferred. If you are studying both subjects then A* can be in either subject. Other preferred subjects include Chemistry, Economics, Physics and Statistics.
Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.
This programme does not accept resits. A resit is a second or subsequent attempt to improve a qualification outcome, for which you already hold an award. For further information on what UCL considers a resit, please see UCAS explained.
Access and widening participationUCL is committed to widening access to higher education. If you are eligible for Access UCL you do not need to do anything in addition to the standard UCAS application. Your application will be automatically flagged when we receive it.
Undergraduate Preparatory Certificates
The Undergraduate Preparatory Certificates (UPC) prepare international students for a UCL undergraduate degree who don’t have the qualifications to enter directly. These intensive one-year foundation courses are taught on our central London campus.
Typical UPC students will be high achievers in a 12-year school system which does not meet the standard required for direct entry to UCL.
For more information see: ucl.ac.uk/upc.
English language requirements
The English language level for this programme is: Level 2
Information about the evidence required, acceptable qualifications and test providers can be found on our English language requirements page.
A variety of English language programmes are offered at the UCL Centre for Languages & International Education.
The programme does not assume any previous exposure to probability, statistics or computer science. During the course of your degree, theoretical studies are balanced with an emphasis on practical work, including the training on at least two programming languages, and realistic illustration of theoretical concepts.
The first year is designed to provide all students with a firm foundation in these subjects, while deepening the knowledge and understanding of those students with some previous exposure to the subject areas: you will study mathematics, statistics and computing, which will prepare you for increased specialisation in data science in years two and three.
The second and third years build on this foundation through further compulsory modules on core topics in probability theory, statistical inference and algorithms. Specialist areas of application, such as in medicine and commerce, are mostly introduced as third year options, although an introductory module in applied science may be taken as early as the first year.
In the final year, there is considerable flexibility to bias your programme towards either the more mathematical or applied aspects of the subject. In particular, about one-quarter of your work will be on a project involving extensive research supervised by a member of staff within the Department of Statistical Science.
What this course will give you
The degree programme is aimed at providing the core capabilities of a data scientist who will be able to engage with a variety of disciplines, from health research, to the digital economy and finance, natural sciences and more.
During the degree programme, students will be exposed to a mix of multidisciplinary modules including in the applied sciences and its data-analytic aspects.
The department offers a friendly and supportive atmosphere, where small-group teaching and personal attention are available for all students.
Ranked 6th in the UK by the QS World University Rankings by Subject 2023 for Statistics and Operational Research, we offer you an excellent education with high standards of teaching.
The structure of the programme encourages hands-on assignments and an interaction with disciplines outside the department.
Teaching and learning
In each year of your degree you will take a number of individual modules, normally valued at 15 or 30 credits, adding up to a total of 120 credits for the year. Modules are assessed in the academic year in which they are taken. The balance of compulsory and optional modules varies from programme to programme and year to year. A 30-credit module is considered equivalent to 15 credits in the European Credit Transfer System (ECTS).
Upon successful completion of 360 credits, you will be awarded a BSc (Hons) in Data Science.
Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability is subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.
The programme does not assume any previous exposure to probability, statistics or computer science. The first year is designed to provide all students with a firm foundation in probability, statistics and computer science. The second and third years build on this foundation through further compulsory modules on core topics in probability theory, statistical inference and algorithms. Specialist areas of application, such as in medicine and commerce, are mostly introduced as third year options.
During the course of your degree, theoretical studies are balanced with emphasis on practical work, including the training on at least two programming languages, and realistic illustration of theoretical concepts. In the final year, there is considerable flexibility to bias your programme towards either the more mathematical or applied aspects of the subject. In particular, about one-quarter of your work will be on a project involving extensive research supervised by a member of staff within the Department of Statistical Science.
We employ a variety of teaching methods which include lectures, small-group tutorials, problem classes and computer workshops and e-learning. Lecturers have regular 'drop-in hours' during which you are welcome to come and ask questions about the programme material.
Contact time will vary according to options chosen, but students will typically be expected to undertake 35-40 hours of study per week, of which they can expect to spend around 20-30% of their time in lectures, 10-20% of their time in tutorials, workshops or computer practicals, and the remainder in independent study.
Most Statistical Science modules employ a combination of end-of-year written examination and coursework to assess your subject-specific knowledge and academic skills, although some modules are entirely coursework based.
The foundation of your career
The programme is also designed to provide you with a preparation for postgraduate study in statistics, machine learning and other specialised fields in applied data science.
Together with subject-specific knowledge, the programme is designed to equip you with skills valued by employers including: advanced numeracy and quantitative skills, analytical and problem-solving skills, and computing skills. You will also develop your research and communication skills through project work.
As a graduate of the programme, you should be able to proceed directly to a post as a data scientist in industry, commerce or government. The skills you will acquire could also be applied to the founding or management of businesses relating to a broad set of data analytic services.
This programme is accredited by the Royal Statistical Society for students who first enrol between September 2023 and September 2028.
Fees and funding
Fees for this course
|Tuition fees (2024/25)
|Tuition fees (2024/25)
The fees indicated are for undergraduate entry in the 2024/25 academic year. The UK fees shown are for the first year of the programme at UCL only. Fees for future years may be subject to an inflationary increase. The Overseas fees shown are the fees that will be charged to 2024/25 entrants for each year of study on the programme, unless otherwise indicated below.
Full details of UCL's tuition fees, tuition fee policy and potential increases to fees can be found on the UCL Students website.
This programme does not have any additional costs outside of purchasing books or stationery, printing, thesis binding or photocopying.
A guide including rough estimates for these and other living expenses is included on the UCL Fees and funding pages. If you are concerned by potential additional costs for books, equipment, etc., please get in touch with the relevant departmental contact (details given on this page).
Funding your studies
The department offers an undergraduate scholarship, the EJ Gumbel Scholarship.
Various funding options are available, including student loans, scholarships and bursaries. UK students whose household income falls below a certain level may also be eligible for a non-repayable bursary or for certain scholarships. Please see the Fees and funding pages for more details.
The Scholarships and Funding website lists scholarships and funding schemes available to UCL students. These may be open to all students, or restricted to specific nationalities, regions or academic department.
We are seeking applicants with a clear interest in Statistics and Mathematics, who have real curiosity and a joy in solving problems, and a motivation to explore topics at the forefront of knowledge.
How to apply
Application for admission should be made through UCAS (the Universities and Colleges Admissions Service). Applicants currently at school or college will be provided with advice on the process; however, applicants who have left school or who are based outside the United Kingdom may obtain information directly from UCAS.
For further information on UCL's selection process see: How we assess your application.
UCL is regulated by the Office for Students.