The world of data science is constantly evolving; when applying for further studies in this field, it is important to ensure that the programme of your choice is compatible with your skills and interests. Staying at the forefront of this dynamic field requires not just theoretical knowledge but also practical and real-world skills. This is precisely where the MSc Data Science programme at LSE stands out as an exceptional path for aspiring data scientists. As a current student of this programme, I would love to share my insights on everything it has to offer.

The curriculum

The curriculum is meticulously designed to reflect the recent advancements in data science, and the core modules which focus on statistical theory provide a strong theoretical base to students. My three core modules include Data Analysis and Statistical Methods, Managing and Visualising Data and Machine Learning and Data Mining, which cover all the fundamental aspects of data science techniques and statistical analysis.

Students are also offered a diverse range of elective courses, allowing them to effectively tailor their learning experience to pursue studies in areas of their interest. My optional courses include Artificial Intelligence, Distributed Computing for Big Data and Deep Learning. A full list of the optional courses offered can be found on the LSE website.

Creating real-world impact

The most unique feature of the programme is that it provides the invaluable prospect of doing a capstone project which is conducted in partnership with major industry experts such as Facebook, Capgemini, Deutsche Bank, etc. The topic for a capstone project is similar to the kinds of data-based issues faced in practice by private or public sector organisations which helps provide students with experience in solving real-world problems in cooperation with an industry partner. 

The project is jointly supervised by the LSE faculty and company partner collaborators. Thus, this course provides students not only with relevant skills but also gives access to unparalleled networking opportunities, laying the groundwork for future career success.

Support from the department

The supportive environment provided by an institution contributes significantly to the success of its students. The various socialising events organised by the Department of Statistics, such as networking opportunities and academic trips, ensure a well-rounded learning experience. 

All professors have office hours during which students can get academic guidance, receive feedback on their progress or even engage in discussions about interesting topics related to the programme. Each student is also assigned an academic mentor (the academic mentor for master’s students is the programme director of the course) who offers guidance and support for both academic and personal concerns. I have spoken to my academic mentor regarding my courses and he has offered me great advice, which helps me pace my studies and excel in them.

Pursuing data science in London

LSE is located in the heart of London which makes studying here an unparalleled experience. The city itself becomes an extension of the classroom and, for data science students, London is an ideal location as it is the hub for various tech companies, startups, and multinational corporations. Outside of the classroom, students can attend many conferences and networking events to connect with industry professionals and gain practical insights in this field.

There is, of course, also the added advantage of getting to explore the beautiful city with friends and colleagues to unwind and de-stress – which, for students in master’s programmes, is definitely a must!

In conclusion, pursuing a MSc Data Science at LSE means academic excellence, a strong network, extracurricular engagement and personal growth. As I continue my journey at LSE and prepare to embark on my career, I am confident that the skills and experiences gained here will serve as a strong foundation for a successful and impactful future in the field of data science.

Apply to the MSc Data Science