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BSc in Data Science

Page contents > Options list | Paper 10 options list | Papers 10 & 11 options list | Prerequisite Requirements and Mutually Exclusive Options | Footnotes

Programme Code: UBDSC

Department: Statistics

For students starting this programme of study in 2022/23

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.

Paper

Course number, title (unit value)

LSE100

LSE100 is a half unit taken by all students, running across Michaelmas and Lent 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 avert climate catastrophe? (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)

Year 1

Paper 1

ST102 Elementary Statistical Theory (1.0) #

Paper 2

MA100 Mathematical Methods (1.0) #

Paper 3

ST101 Programming for Data Science (0.5) # and ST115 Managing and Visualising Data (0.5) #

Paper 4

EC1A3 Microeconomics I (0.5) #

 

and one from:

 

EC1B3 Macroeconomics I (0.5) #

 

FM101 Finance (0.5)

Year 2

Paper 5

MA102 Mathematical Proof and Analysis (0.5) # A

 

and

 

MA222 Further Mathematical Methods (Linear Algebra) (0.5) #

Papers 6 & 7

Courses to the value of 2.0 unit(s) from the following:

 

Either

 

ST206 Probability and Distribution Theory (0.5) # and ST211 Applied Regression (0.5) #

 

and 1.0 unit(s) from the options list below

 

Or

 

ST202 Probability, Distribution Theory and Inference (1.0) # and ST211 Applied Regression (0.5) #

 

and 0.5 unit(s) from the options list below

Options list

Paper 8

MA214 Algorithms and Data Structures (0.5) # and ST207 Databases (0.5) #

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:

 

ST300 Regression and Generalised Linear Models (0.5) #

 

ST304 Time Series and Forecasting (0.5) #

 

ST308 Bayesian Inference (0.5) #

 

ST326 Financial Statistics (0.5) #

Paper 11

ST312 Applied Statistics Project (0.5) #

 

and 0.5 unit(s) from the list of options below

 

List of options

 

MA301 Mathematical Game Theory (0.5) #

 

MA316 Graph Theory (0.5) #

 

MA320 Mathematics of Networks (0.5) #

 

MA324 Mathematical Modelling and Simulation (0.5) #

 

MA333 Optimisation for Machine Learning (0.5) #

 

ST301 Actuarial Mathematics (Life) (0.5) # 1

 

ST302 Stochastic Processes (0.5) #

 

ST303 Stochastic Simulation (0.5) # 2

 

ST307 Aspects of Market Research (0.5) # 3

 

ST313 Ethics for Data Science (0.5) #

 

any 0.5 unit(s) course listed under paper 10

Paper 10 options list

Paper 12

Courses to the value of 1.0 unit(s) from the following:

 

FM213 Principles of Finance (1.0) #

 

FM300 Corporate Finance, Investments and Financial Markets (1.0) # 4

 

MA330 Game Theory for Collective Decisions (0.5) #

 

ST313 Ethics for Data Science (0.5) #

 

ST327 Market Research: An Integrated Approach (1.0) # 5

 

ST330 Stochastic and Actuarial Methods in Finance (1.0) # 6

 

any courses listed under papers 10 & 11

Papers 10 & 11 options list

Options list

EC2A3 Microeconomics II (0.5) #

EC2B3 Macroeconomics II (0.5) #

EC2C3 Econometrics I (0.5) #

EC2C4 Econometrics II (0.5) #

FM213 Principles of Finance (1.0) #

LL210 Information Technology and the Law (1.0) #

MA103 Introduction to Abstract Mathematics (1.0) # B

MA208 Optimisation Theory (0.5) #

MA210 Discrete Mathematics (0.5) #

MA213 Operations Research Techniques (0.5) #

ST205 Sample Surveys and Experiments (0.5) #

ST226 Actuarial Investigations: Financial (0.5) #

ST227 Survival Models (0.5) #

Paper 10 options list

ST300 Regression and Generalised Linear Models (0.5) #

ST304 Time Series and Forecasting (0.5) #

ST308 Bayesian Inference (0.5) #

ST326 Financial Statistics (0.5) #

Papers 10 & 11 options list

MA301 Mathematical Game Theory (0.5) # 7

MA316 Graph Theory (0.5) #

MA320 Mathematics of Networks (0.5) #

MA324 Mathematical Modelling and Simulation (0.5) #

MA333 Optimisation for Machine Learning (0.5) #

ST300 Regression and Generalised Linear Models (0.5) #

ST301 Actuarial Mathematics (Life) (0.5) # 8

ST302 Stochastic Processes (0.5) #

ST303 Stochastic Simulation (0.5) # 9

ST304 Time Series and Forecasting (0.5) #

ST307 Aspects of Market Research (0.5) # 10

ST308 Bayesian Inference (0.5) #

ST326 Financial Statistics (0.5) #

Prerequisite Requirements and Mutually Exclusive Options

1 : Before taking ST301 you must take ST227

2 : Before taking ST303 you must take ST302

3 : ST307 can not be taken with ST205, ST327

4 : Before taking FM300 you must take FM213

5 : ST327 can not be taken with ST307

6 : Before taking ST330 you must take ST302

7 : MA301 can not be taken with MA300

8 : Before taking ST301 you must take ST227

9 : Before taking ST303 you must take ST302

10 : ST307 can not be taken with ST327, ST205

Footnotes

A : Students can obtain exemption from this course if they take MA103 in papers 6&7

B : Students taking this option are exempt from MA102

# 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.

 
 
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