What will I learn?

The MSc Data Science provides training in data science methods, emphasising statistical perspectives. You will receive a thorough grounding in theory, as well as the technical and practical skills of data science. Your theoretical learning will be at a high mathematical level, while the technical and practical skills you will gain will enable you to apply advanced methods of data science and statistics to investigate real world questions.

The compulsory courses on the MSc Data Science programme will provide you with comprehensive coverage of some fundamental aspects of data, computational techniques and statistical analysis. You will then choose courses from a number of options ranging from Articifical Intelligence and Deep Learning, Bayesian Machine Learning and Distributed Computing for Big Data, to Financial Statistics and Statistical Computing. The programme will combine traditional lectures with computer lab sessions, in which you will work with data to complete hands-on exercises using programming tools.

The MSc Data Science Capstone Project will provide you with a unique opportunity to apply knowledge gained from the programme by working on a real-world data science project in cooperation with a company. The Capstone Project company partners in the academic year 2018/19 included Adobe Research, Alpha Telefonica, Facebook, Microsoft, and Tesco. The Capstone Projects have covered a wide range of data science problems involving analysis of various types of data such as social media data, customer behaviour data, and company network data. Working on a Capstone Project will enable you to gain valuable hands-on experience and interact with industry.

Teaching methods

LSE is internationally recognised for its teaching and research and therefore employs a rich variety of teaching staff with a range of experience and status. Courses may be taught by individual members of faculty, such as lecturers, senior lecturers, readers, associate professors and professors. Many departments now also employ guest teachers and visiting members of staff, LSE teaching fellows and graduate teaching assistants who are usually doctoral research students and in the majority of cases, teach on undergraduate courses only.

Assessment

All taught courses are required to include formative coursework which is unassessed. It is designed to help prepare you for summative assessment which counts towards the course mark and to the degree award.

The programme will incorporate diverse forms of summative assessment, including some conventional assessment by written examination in summer term, but also a range of other kinds of assessment of varying size, reflecting the fundamentally computational nature of the subject matter.

There will be shorter take-home exams for which an invigilated exam would be unrealistic given the computer applications involved. There will be smaller projects, both individual-based and group-based, which enable practical problem-based learning to take place.

Finally, the capstone project/dissertation will assess your ability to take on large-scale data-based problem solving.

Careers

Data scientists are much in demand across industry, including a variety of Internet online service companies, marketers, banks, investment management, and other financial companies.

Data scientist positions involve a wide range of responsibilities; such as conducting exploratory data analysis, applying statistical methodologies, deriving business insights from data, partnering with company executives, product and engineering teams to solve problems, identify trends and opportunities, inform, influence, support, and execute product decisions and launches.

Which department am I in?

London School of Economics and Political Science, University of London

Study options

Full Time (1 year)

Tuition fees
£30,960.00 (US$ 42,597) per year
This is a fixed fee
Start date

Expected September 2022

Venue

Houghton Street

London School of Economics and Political Science,

London,

England,

WC2A 2AE, England

Entry requirements

For students from United States

Students need a bachelor's degree with a GPA of 3.5/4, or 4.3/5 or 85 per cent overall. If the only grading scheme used is a letter-grade system, we would normally require a B+ average. Applications are considered on an individual basis and entry requirements vary by programme.

For international students

Students need to have a Upper second class honours (2:1) degree or equivalent in a relevant discipline, including a substantial amount of mathematics. Students need to have: an IELTS score of 7.0 overall (Reading 6.5, Listening 6.5, Writing 6.5, Speaking 6.5); TOEFL 100 (Reading 23, Listening 22, Writing 24, Speaking 22).

*There may be different IELTS requirements depending on your chosen course.

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