Data Science

The degree involves studying courses to the value of 12 units over three years, plus LSE100. 

First year

In your first year, you will take six compulsory courses. In addition, you will also take LSE100.

(* denotes a half unit course)

Elementary Statistical Theory  
This is a theoretical statistics course which is appropriate whether or not your A level Mathematics course included statistics. It forms the basis for later statistics options.

Mathematical Methods  
This is an introductory-level "how to do it" course designed to prepare you for using mathematics seriously in the social sciences, or any other context.

Programming for Data Science*
Covers the principles of computer programming with a focus on data science applications.

Managing and Visualising Data*
Explains the fundamental principles for effective manipulation and visualisation of data.

Microeconomics I* 
Introduces the principles of microeconomics analysis. You will study the foundations of consumer and producer theory, competitive and monopolistic markets, welfare analysis and taxation, market failure, as well as an introduction to game theory. 

One from:

Macroeconomics I* 
Provides an introduction to macroeconomic analysis, you will study how countries' economic performance is determined in the short and the long run.

Finance* 
Delivers an introduction to the financial decisions of firms, in particular capital budgeting; the financial decisions of households; the role of the financial system in the economy and the flow of funds; causes and consequences of the recent financial crises.

LSE100*
A half unit, running across Michaelmas and Lent Term in the first year, LSE100 is compulsory for all LSE undergraduate students, and is designed to build your capacity to tackle multidimensional problems through research-rich education.

Second year

In your second year you will take a mixture of core and optional courses.

Mathematical Proof and Analysis* 
Provides an introduction to the use of formal definitions and proofs in mathematics, and to basic results of elementary logic, set theory and analysis. Specific topics covered are as follows: Logic, sets and functions, relations, real numbers, infimum and supremum, sequences, limits and continuity.

Further Mathematical Models (Linear Algebra)*
Covers: Vector spaces and dimension. Linear transformations, kernel and image. Real inner products. Orthogonal matrices, and the transformations they represent. Complex matrices, diagonalisation, special types of matrix and their properties. Jordan normal form, with applications to the solutions of differential and difference equations. Singular values, and the singular values decomposition. Direct sums, orthogonal projections, least square approximations, Fourier series. Right and left inverses and generalized inverses.

Algorithms and Data Structures*
Introduces the fundamental principles of data structures and algorithms and their efficient implementation.

Databases*
Covers the basic concepts of database management systems, including relational and other types of database management systems. 

Either

Probability and Distribution Theory*
Covers the probability, distribution theory and statistical inference needed for third year courses in statistics and econometrics.

AND 

Applied Regression*
Statistical data analysis in R covering the following topics: Simple and multiple linear regression, model diagnostics, detection of outliers, multicollinearity and introduction to GLMs.

AND an optional course to the value of one whole unit

Or

Probability, Distribution Theory and Inference
Develops your knowledge of probability and statistics beyond the first-year course. It will also provide the probability and statistics basis for all third-year courses.

AND

Applied Regression*
Statistical data analysis in R covering the following topics: Simple and multiple linear regression, model diagnostics, detection of outliers, multicollinearity and introduction to GLMs.

AND an optional course to the value of 0.5 units

Third year

In your third year you will take three compulsory courses, and will choose options to the value of two units.

Machine Learning*
Focuses on the core machine learning techniques in the context of high-dimensional or large datasets (i.e. big data).

Artificial Intelligence*
Introduces the basic principles of artificial intelligence systems.

Applied Statistics Project*
Involves a critical investigation and collation of statistical data on a topic of your own interest.

Courses to the value of one unit from the below options:

Regression and Generalised Linear Models*
Covers the most important parts of the theory and application of regression models and generalised linear models.

Time Series and Forecasting*
Introduces the statistical analysis of time series data and simple models, and showcases what time series analysis can be useful for.

Bayesian Inference*
Examines statistical decision theory, Bayesian inference, implementation and applications.

Financial Statistics*
Covers key statistical methods and data analytic techniques most relevant to finance.

Optional course to the value of 1.5 units

For the most up-to-date list of optional courses please visit the relevant School Calendar page.

Where regulations permit, you may also be able to take a language, literature or linguistics option as part of your degree. Information can be found on the Language Centre webpages.

You must note however that while care has been taken to ensure that this information is up-to-date and correct, a change of circumstances since publication may cause the School to change, suspend or withdraw a course or programme of study, or change the fees that apply to it. The School will always notify the affected parties as early as practicably possible and propose any viable and relevant alternative options. Note that the School will neither be liable for information that after publication becomes inaccurate or irrelevant, nor for changing, suspending or withdrawing a course or programme of study due to events outside of its control, which includes but is not limited to a lack of demand for a course or programme of study, industrial action, fire, flood or other environmental or physical damage to premises.

You must also note that places are limited on some courses and/or subject to specific entry requirements. The School cannot therefore guarantee you a place. Please note that changes to programmes and courses can sometimes occur after you have accepted your offer of a place. These changes are normally made in light of developments in the discipline or path-breaking research, or on the basis of student feedback. Changes can take the form of altered course content, teaching formats or assessment modes. Any such changes are intended to enhance the student learning experience. You should visit the School's Calendar, or contact the relevant academic department, for information on the availability and/or content of courses and programmes of study. Certain substantive changes will be listed on the updated undergraduate course and programme information page.

Quick Careers Facts for the Department of Statistics

Median salary of our UG students six months after graduating: £35,000

Top 5 sectors our students work in:

• Financial and Professional Services
• Accounting and Auditing
• Consultancy
• Government, Public Sector and Policy
• Insurance

The data was collected as part of the Graduate Outcomes survey, which is administered by the Higher Education Statistics Agency (HESA). Graduates from 2018-19 were the second group to be asked to respond to Graduate Outcomes. Median salaries are calculated for respondents who are paid in UK pounds sterling and who were working in full-time employment.

Graduates from the programme will be prepared for further study, or for professional and managerial careers, particularly in areas requiring the application of quantitative skills. 

Further information on graduate destinations for this programme

Support for your career

Many leading organisations give careers presentations at the School during the year, and LSE Careers has a wide range of resources available to assist students in their job search.