The MSc Data Science degree offers in-depth training at the forefront of machine learning and data science. The programme is available full-time for both Home and Overseas students, and part-time for Home students. We seek applicants with a solid quantitative background and a strong interest in statistics, mathematics, and programming.
The programme offers a unique opportunity for prospective students: the theoretical foundations and computational skills you'll acquire will enable you to deploy state-of-the-art data science methods and gain a thorough understanding to tackle various real-world challenges across different application domains at scale. The programme's integration within LSE will also guide your attention towards socially relevant and impactful problems.
The curriculum requires four mandatory courses, including a Capstone project, and three elective courses. The compulsory courses cover fundamental aspects of modern data analysis from both computational and statistical perspectives. The optional courses will enrich you with additional in-depth knowledge in areas such as Artificial Intelligence, Deep Learning, Reinforcement Learning, Bayesian Machine Learning, Distributed Computing for Big Data, Graph Data Analytics and Representation Learning, Time Series Analysis, and Financial Statistics. During the computer seminars accompanying the lectures, you'll gain hands-on experience in numerous applications and develop skills in using modern computing systems and software frameworks.
Within the Capstone Project, you'll have the opportunity to apply your acquired skills to real-world data science problems in a team and to interact directly with industry partners. You'll be jointly supported by one of our industrial partners and an academic with leading expertise from the department. In recent years, our Capstone Project partners have included companies such as Google, Microsoft, Facebook/Meta, Adobe, Samsung, Koa Health, AstraZeneca, Capgemini, Siemens Advanta Consulting, ADIA, Wise, Deutsche Bank, Houghton Street Ventures, Experian DataLabs, KPMG, Tesco, Plymouth Marine Laboratory, Alpha Telefónica, Westminster City Council, and the Thames Valley Violence Reduction Unit. Our capstone projects covered a wide range of application domains, including healthcare, marine and climate research, sustainability, agriculture, transportation, logistics, student well-being, entrepreneurship, and finance.
Discover more about our students and department.
The Department of Statistics at LSE is one of the oldest and most distinguished in the UK.
The department has an international reputation for the development of statistical methodology and a long history of pioneering contributions to research and teaching. Many of the world’s most famous and innovative statisticians have been associated with LSE.
Our research spans four main areas – data science , probability in finance and insurance , social statistics , and time series and statistical learning . The department has close links with the Data Science Institute at LSE – an interdisciplinary institute that fosters the study of data science, with a particular emphasis on the social, economic and political contexts.
All aspects of our research were ranked world-leading or internationally excellent in the most recent Research Excellence Framework (2021) , submitted jointly with the Department of Mathematics .
The department’s research strengths are reflected in our teaching curriculum. We have a comprehensive range of undergraduate and postgraduate degrees and doctoral research opportunities – hosted in a vibrant department with a supportive and friendly community of staff and students.
Our alumni enjoy successful careers in diverse areas, such as banking, accounting, finance, statistics, government and business consulting while others pursue postgraduate study or research. Our alumni frequently return to LSE to share their career experiences with current students.
Upper second class honours (2:1) degree or equivalent in a relevant discipline, including a substantial amount of mathematics.
Please select your country from the dropdown list below to find out the entry requirements that apply to you.
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The English language requirement for this programme is Standard . Read more about our English language requirements .
Competition for places at LSE is strong. So, even if you meet the minimum entry requirements, this doesn't guarantee you an offer of a place.
However, please don’t feel deterred from applying – we want to hear from all suitably qualified students. Think carefully about how you can put together the strongest possible application to help you stand out.
| QS 综合 | 院校 | 学制 | 学费 |
|---|---|---|---|
| 第 8 位 | 伦敦大学学院University College London | 1年 | 48600英镑/年 |
| 第 8 位 | 苏黎世联邦理工学院ETH Zurich | 2年 | 1460瑞士法郎/年 |
| 第 12 位 | 南洋理工大学Nanyang Technological University | 1年 | 65749新币/年 |
| 第 22 位 | 洛桑联邦理工学院EPFL | 2年 | 1460瑞士法郎/年 |
| 第 35 位 | 爱丁堡大学The University of Edinburgh | 1年 | 47680英镑/年 |
| 第 37 位 | 伦敦国王学院King's College London | 1年 | 42900英镑/年 |
| 第 52 位 | 香港城市大学City University of Hong Kong | 1年 | 342000港币/年 |
| 第 57 位 | 布里斯托大学University of Bristol | 1年 | 37900英镑/年 |