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Декан — Аржанцев Иван Владимирович
Первый заместитель декана факультета — Вознесенская Тамара Васильевна
Заместитель декана по научной работе и международным связям — Объедков Сергей Александрович
Заместитель декана по учебно-методической работе — Самоненко Илья Юрьевич
Заместитель декана по развитию и административно-финансовой работе — Плисецкая Ирина Александровна
Факультет готовит разработчиков и исследователей. Программа обучения сформирована с учётом опыта ведущих американских и европейских университетов, таких как Stanford University (США) и EPFL (Швейцария), а также Школы анализа данных — одной из самых сильных магистратур в области computer science в России. Широкий список курсов по выбору и значительная доля программы, выделенная под них, позволит каждому студенту сформировать свою собственную образовательную траекторию. В основе обучения — практика и проектная работа.
Bienvenu M., Kikot S., Kontchakov R. et al.
Journal of the ACM. 2018. Vol. 65. No. 5. P. 28:1-28:51.
Doikov Nikita, Richtarik P.
Proceedings of Machine Learning Research. 2018. No. 80. P. 1290-1298.
Hushchyn M., Chekalina V.
Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2018. P. 1-2.
Naumov A., Spokoiny V., Ulyanov V. V.
Probability Theory and Related Fields. 2019. P. 1-42.
Shapoval A., Le Mouël J., Shnirman M. et al.
Astronomy and Astrophysics. 2018. Vol. 618. P. A183-1-A183-13.
Интерес абитуриентов к новому бакалавриату ВШЭ и LSE “Прикладной анализ данных” оказался выше ожидаемого. Было принято решение увеличить количество мест на программу с изначальных 50 до 80. Джеймс Абди, руководитель программы “Data Science and Business Analytics” с британской стороны, рассказал о своем видении концепции программы, востребованности будущих выпускников и преимуществах, которые дает двойной диплом. Материал публикуется на английском языке.
James is a programme convenor of “Data Science and Business Analytics”, a Lecturer in Statistics at the London School of Economics and Political Science (LSE), having gained his PhD in Statistics in 2010 from LSE, asking "To p, or not to p?"! He teaches the Department's undergraduate courses in mathematical statistics and quantitative methods, as well as elective courses in market research. His research interests include market research techniques and forensic statistics - the interplay of statistics and the law. Outside of academia, he has also worked on various quantitative-based consultancy projects in areas including the art market, the World Gold Council and has given seminars at the UK parliament.
Why has LSE decided to develop the Data Science and Business Analytics programme?
As the world becomes ever-more data-driven, it is only right that our degree programmes evolve to meet the demands of a changing labour market. Quantitative skills are a huge asset in the workplace, so we decided to create our innovative BSc Data Science and Business Analytics (DSBA) degree to help maximise the career potential of our graduates. The fields of data science as well as business analytics are being seen more frequently at Masters level, but there is a severe lack of high-quality undergraduate provision in this field. The LSE-led University of London programmes are delighted to offer students the opportunity to pursue the development of strong analytical skills at HSE.
What does the Computer Science Faculty at HSE contribute to the double-degree program?
HSE's excellent Computer Science faculty are well-placed to contribute to the delivery of the programme by allowing students to tap in to the expertise of the faculty in terms of their skills in applied mathematics and programming. An invaluable data scientist is one who can demonstrate a broad skill set including aspects of computer science alongside mathematics and statistics. While only founded in 2014, the faculty size is formidable and offers a stimulating environment for students.
What, in your opinion, is the uniqueness of this program?
Blending quantitative expertise with some qualitative insights, graduates of the DSBA programme will be among the world's first graduates in this area due to undergraduate provision of such programmes being in its infancy. With strong employer demand for graduates with skills embedded in DSBA, and a limited supply of graduates, students pursuing the degree will surely gain a competitive edge in the labour market. Also, being a dual-degree programme, students walk away with two degree certificates instead of one, each issued by universities with strong international reputations - the best of both worlds !
How is LSE going to support the program?
LSE provides the academic direction for the degree. This means we design each module, developing the curriculum and learning materials. Academics in London also set and mark the examinations, ensuring quality control of the assessment process. Direct interaction with our partner teaching centres and students is an important aspect of the relationship, and visits to HSE represent a vital, and highly visible, avenue of support.
This is not the first time that LSE and HSE create a dual-degree program. Why, would you say, is this collaboration successful?
In addition to the similar acronyms(!), LSE and HSE are a natural fit for collaboration. Central to both institutions is the desire for academic excellence, with research-informed teaching helping our students reach their full academic potential. Indeed, the higher education sector is becoming increasing globalised with transnational education increasingly common. Our successful history of running dual-degree programmes means we are very excited to expand our collaboration with the provision of DSBA.
For whom would you, first of all, recommend this program?
Any student with a quantitative flair and a desire to apply mathematical and statistical techniques to analysing real-world business problems should definitely apply! The DSBA programme blends theoretical and applied content preparing students for an exciting career in the field. In particular, potential students keen on working internationally will value the University of London degree award which is globally recognised and will open up numerous employment opportunities as well as options for postgraduate study.
Why do companies need experts, who possess the necessary skills for Data Analysis? Why isn't it enough to employ business analysts on the one hand and data scientists on the other?
I think we shouldn't necessarily treat data science and business analytics as being mutually exclusive fields, rather they have strong complementary features. Usually students face the trade-off between breadth and depth of study, however DSBA is designed to deliver both. Inevitably, this means an intellectually rigorous and demanding programme of study, but therein lies its strength. By combining expertise in data science and business analytics, our graduates will be able to offer a holistic understanding, as well as a technical understanding of quantitative problems.
Among which British and international companies will the graduates be in demand?
Companies and industries employing our graduates are so varied that you are really only limited by your imagination in terms of where you could end up working. Sectors including the financial, retail, pharmaceutical, logistics and even the public sector are possible employment destinations. Appreciate, though, that the labour market is ever-evolving and new sectors could even be on the horizon. It is an exciting, and brave new world for today's graduates.
How will the UoL degree graduates be able to pursue further higher education?
Increasingly many graduates opt for postgraduate study. Pursuing a Masters degree enables students to gain a deeper exposure to their discipline of interest. Upon successful completion of the dual-degree programme, students will be excellently-placed to undertake Masters study at top institutions worldwide. Content studied at undergraduate level will equip you with a solid foundation in data science and business analytics, on which it is possible to develop even higher-order skills.