BSc in Data Science

Programme Code: UBDSC

Department: Statistics

For students starting this programme of study in 2026/27

Guidelines for interpreting programme regulations

Three-year Classification Scheme for BA/BSc degrees from the 2018/19 academic year.

Please note that places are limited on some optional courses. Admission onto any particular course is not guaranteed and may be subject to timetabling constraints and/or students meeting specific prerequisite requirements.
	Course code, title (unit value)
Year 1
LSE100	LSE100 is a half unit taken by all students, running across Autumn and Winter Terms in the first year. The course provides one of the marks that is eligible to be included in the calculation of the First Year Average for purposes of classification. Students will choose ONE of the three half-unit options below: LSE100A The LSE Course: How can we transform our climate futures? (0.5)
	LSE100B The LSE Course: How can we control AI? (0.5)
	LSE100C The LSE Course: How can we create a fair society? (0.5)

Paper 1	ST102 Elementary Statistical Theory (1.0) #

Paper 2	MA100 Mathematical Methods (1.0) #

Paper 3	ST101A Programming for Data Science (0.5)
	ST115 Managing and Visualising Data (0.5) #

Paper 4	Courses to the value of 0.5 unit(s) from the following:
	AC102 Elements of Financial Accounting (0.5)
	EC1A3 Microeconomics I (0.5) #
	MA102 Mathematical Proof and Analysis (0.5) #
	AND Courses to the value of 0.5 unit(s) from the following: AC103 Elements of Management Accounting, Financial Management and Financial Institutions (0.5)
	EC1B3 Macroeconomics I (0.5) #
	FM101 Finance (0.5)
	MA104 Abstract Mathematics and Algorithms (0.5) #

Year 2
Paper 5	ST206 Probability and Distribution Theory (0.5) # and ST211 Applied Regression (0.5) #
Paper 6	MA214 Algorithms and Data Structures (0.5) # and ST207 Databases (0.5) #
Paper 7	MA222 Further Mathematical Methods (Linear Algebra) (0.5) #
	and (If MA102 has not been taken in Year 1): MA102 Mathematical Proof and Analysis (0.5) #
	(OR) (If MA102 has been taken in Year 1) one from: MA203 Real Analysis (0.5)
	MA221 Further Mathematical Methods (Calculus) (0.5) #

Paper 8	Courses to the value of 1.0 unit(s) from the following: Options list
Year 3
Paper 9	ST310 Machine Learning (0.5) # and ST311 Artificial Intelligence (0.5) #
Paper 10	Courses to the value of 1.0 unit(s) from the following:
	Statistics options list 1
Paper 11	ST312 Applied Statistics Project (0.5) #
	Statistics options list 1
	Statistics options list 2
	Mathematics options list
Paper 12	Courses to the value of 1.0 unit(s) from the following:
	Statistics options list 1
	Statistics options list 2
	Mathematics options list
	Other options list

Options list



EC2A3 Microeconomics II (0.5) #
EC2B3 Macroeconomics II (0.5) #
EC2C3 Econometrics I (0.5) #
EC2C4 Econometrics II (0.5) #
FM214 Principles of Finance I (0.5) #
FM215 Principles of Finance II (0.5)
LL210 Information Technology and the Law (1.0) # (withdrawn 2026/27)
LL220 Technology Law and Regulation (0.5) #
MA203 Real Analysis (0.5)
MA208 Optimisation Theory (0.5) #
MA210 Discrete Mathematics (0.5) #
MA213 Operations Research Techniques (0.5) #
MA221 Further Mathematical Methods (Calculus) (0.5) #
ST205 Sample Surveys and Experiments (0.5) #
ST216 Statistical Inference (0.5) # A
ST226 Mathematics for Finance and Investment (0.5) #
ST227 Survival Models (0.5) #

Footnote for Options list

A: ST216: Before taking ST216, you must take ST206.

Statistics options list 1



ST300 Regression and Generalised Linear Models (0.5) #
ST301 Actuarial Mathematics (Life) (0.5)
ST302 Stochastic Processes (0.5)
ST304 Time Series and Forecasting (0.5) #
ST308 Bayesian Inference (0.5) #
ST314 Multilevel and Longitudinal Models (0.5) #
ST326 Financial Statistics (0.5) #
ST330 Stochastic and Actuarial Methods in Finance (1.0)

Statistics options list 2



ST303 Stochastic Simulation (0.5) #
ST307 Aspects of Market Research (0.5) #
ST313 Ethics for Data Science (0.5) #
ST327 Market Research: An Integrated Approach (1.0)

Mathematics options list



MA301 Mathematical Game Theory (0.5) #
MA316 Graph Theory (0.5) #
MA320 Mathematics of Networks (0.5)
MA324 Mathematical Modelling and Simulation (0.5) #
MA330 Game Theory for Collective Decisions (0.5) #
MA333 Optimisation for Machine Learning (0.5) #

Other options list



EC2A3 Microeconomics II (0.5) #
EC2B3 Macroeconomics II (0.5) #
EC2C3 Econometrics I (0.5) #
EC2C4 Econometrics II (0.5) #
FM214 Principles of Finance I (0.5) #
FM215 Principles of Finance II (0.5)
FM310 Corporate Finance, Investments and Financial Markets I (0.5)
FM311 Corporate Finance, Investments and Financial Markets II (0.5)
FM321 Risk Management and Modelling (0.5) #
FM322 Derivatives (0.5) #

Footnotes

# means there may be prerequisites for this course. Please view the course guide for more information.

Note for prospective students:
For changes to undergraduate course and programme information for the next academic session, please see the undergraduate summary page for prospective students. Changes to course and programme information for future academic sessions can be found on the undergraduate summary page for future students.