HSE Winter School on Analytics and Data Science Brings Together Specialists in Different Fields
In early February, the HSE Cultural Centre hosted ‘IT Session: Immersion in the Data World’, a winter school on analytics and data science organised by the Continuing Education Centre of the Faculty of Computer Science. More than four hundred participants attended lectures by speakers from Yandex, T-Bank, MTS, Okko, Kuper, Avito, Bank of Russia, Beeline, as well as FCS experts. The event gathered both early-career analysts and students, as well as experts seeking to better understand how analytics and data science can be applied in various industries.
New Career Opportunities and Various Participants
The school’s participants included specialists who were not directly related to IT but wanted to learn how to apply data analysis in their current activities. There were also students who plan to engage in data science and want to find an optimal career path. Students learnt how theoretical tools can be applied in practice and communicated with industry representatives. The school's programme included several tracks and a variety of presentation formats, from an introductory lecture on trends in analytics and data science to reports on ML tools and applied tasks.
General Track: Main Trends
Daria Kasyanenko, an expert and teacher at the Continuing Education Centre of the Faculty of Computer Science, delivered a welcoming speech at the school’s opening. She provided an overview of important vectors of development in analytics and data science, emphasising the roles of data streaming, integration of artificial intelligence, advanced analytics, and cloud platforms. Daria noted that the development of technological capabilities requires specialists to constantly update their competencies and be ready for the rapid introduction of new technologies.
Industry Parallels: Overview Track and Tools and Technologies
The participants could choose one of two tracks:
Overview Track
Elen Tevanian, Head of ML in Operations at Kuper, showed what kind of ML tasks are solved in the e-com service and how technologies help to increase usability. Anton Skogorev, Technical Director of the T-Bank AI Center, explained how applications based on generative AI are created: from simple single-prompt scenarios to more complex chains of agents.
Alexander Kondrashkin, Head of Analytics at Okko, explained how online cinema works, what tasks analysts solve, and how competent data management benefits businesses.
Tools and Technologies
Ivan Gudkov, Lead Economist at the Bank of Russia, demonstrated the main types of ML tasks in the banking sector and showed how NLP works in financial structures. The participants saw a step-by-step solution to an applied problem and got acquainted with the features of machine learning integration in a large company.
Anton Semenisty, Senior DS Engineer at the Avito Monetization Department, presented a detailed overview of the algorithms used in the platform, from advertising auctions and autobidding to probabilistic models for predicting user targets.
Artur Samigullin, Team Lead at YandexArt, spoke about evaluating the quality of generative models, having considered the features of pointwise and pairwise markup. Using case examples, the speaker examined the difficulties faced by analysts when testing such systems and how they find optimal solutions for various cases.
Big Data and AI
The final report was presented by Alina Sadukevich, Chief Product Officer at Beeline. Alina described the creation of products based on big data and artificial intelligence, and which elements fall into each of these categories.
Networking and Informal Communication
In the evening, the participants had a networking session where they could ask additional questions to the speakers, exchange contacts, and discuss the lectures. In addition, the winners of interactive contests organised within the school received prizes.
Courses and programmes of the Continuing Education Centre of the Faculty of Computer Science will start in the near future.
The online course ‘Programming in Python’ serves as an introduction to one of the most popular modern programming languages. Python with its libraries is a universal tool for solving many applied tasks. Students will learn how to program from scratch, learn the features of Python syntax and how to apply it to solve problems in a wide variety of fields, and master data analysis, visualisation, and data collection from online resources.
The online course ‘SQL for Beginners’ will help students master the SQL language from scratch: basic queries, grouping tables and aggregating functions, working with strings and dates, window functions.
The Data Analyst professional retraining programme covers the study of databases and SQL, as well as Python, its application for data collection, visualisation and analysis, statistics and machine learning, analytical and product approaches to working on tasks.
The Data Science Specialist programme immerses students in modern data analysis and machine learning, from learning programming and basic mathematics to deep learning, applied statistics, and working with big data.
The online course ‘Analytics in Business Intelligence’ is dedicated to working with BI systems using the example of Tableau and DataLens. Students will learn how to use Business Intelligence to visualise and prepare data for further work, as well as how to set up a dashboard that satisfies the customer.
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