Data Science London School of Economics and Political Science

Overview

The Data Science programme at the London School of Economics and Political Science offers students a rigorous foundation in the rapidly evolving fields of machine learning and statistical analysis. This curriculum is designed for individuals with strong quantitative backgrounds who wish to master the technical skills required to solve complex, large-scale problems. By combining theoretical depth with practical application, the university ensures graduates are prepared for the technical demands of modern industry.

Students engage with state-of-the-art data science methods, learning to deploy sophisticated algorithms across various application domains. The programme emphasises socially relevant challenges, encouraging learners to apply their technical expertise to impactful global issues.

Why Data Science at the London School of Economics and Political Science?

The Department of Statistics at the university holds an international reputation for excellence and is one of the oldest and most distinguished in the United Kingdom. Research within the department is ranked as world-leading, ensuring that the teaching curriculum is informed by the latest methodological developments. Students benefit from the department's close integration with the Data Science Institute, fostering an interdisciplinary approach to the subject.

A defining feature of this programme is the Capstone Project, which allows students to tackle real-world data problems in collaboration with industry partners. Recent participants have worked with prestigious organisations such as Google, Microsoft, Meta, and AstraZeneca. These partnerships provide invaluable exposure to professional environments and allow students to apply their skills to diverse sectors, including healthcare, finance, and sustainability.

Tuition Fee Breakdown

• International fee: GBP 38000 per year
• National fee: GBP 38000 per year

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum consists of four mandatory courses and a selection of elective modules. Modules may include:

• Managing and Visualising Data
• Data Analysis and Statistical Methods
• Machine Learning and Data Mining
• Capstone Project
• Artificial Intelligence
• Deep Learning
• Reinforcement Learning
• Bayesian Machine Learning
• Distributed Computing for Big Data

Careers with Data Science

Graduates are highly sought after by a wide range of employers, particularly within internet service companies, investment management firms, and global banks. The roles typically involve conducting exploratory data analysis, applying statistical methodologies, and partnering with engineering teams to influence product decisions. Graduates often find success in sectors such as financial services, digital technology, and professional auditing.