
Study program
The goal of the Summer School is to give the practice-oriented knowledge in the field of Data Science. The school’s program incorporates three following stages. During the first stage, the participants attend introductory courses that would make them familiar with the main theme of the school: Statistical Inference, Machine Learning, Data Visualization. During the second stage, the students are involved in several elective practice-oriented courses in the domains of Computer Vision, Natural Language Processing, Healthcare, Social Network Analysis, Urban Data Science, Recommender Systems, etc. The third stage is substantially dedicated to working on the projects. The project topics are provided by the supervisors: school’s lecturers, representatives of IT companies, and other partner organizations. The project work during several days means implementation and approbation of the previously obtained knowledge and skills. The project teams present their results publicly at the end of the school. The participants can gain 4 ECTS credits after the school completion.Course list
- Keynote lecture (July 16)
- General courses (July 17-21)
- Applied courses (part I, July 23-25)
- Students should select any two courses from the list
- Introduction to Computer Vision
- Natural Language Processing
- Machine Learning in Healthcare
- Machine Learning for Dynamic Social Network Analysis
- Introduction to Urban Data Science
- Advanced customers analytics. Practical use of algorithmic marketing
- Recommender Systems
- Robotics and Machine Learning
- Applied courses (part II, July 26-27)
- Students should select any two courses from the list
- Computer Vision for video understanding and Interpretability of automated decisions
- Applied Sports Analytics
- Applied Econometrics (Macro and Finance)
- GANs and Roses
- Hyper-parameter optimization and model selection in machine learning
- Data Science for Urban Energy
- Data Analysis for Policy Making
- Discrete Computation Graphs
- and some more courses (July 28)
Lecturers
The scientists from well-known universities and the leading specialists of the Ukrainian and world’s companies taught at the summer school.![]() Dr. Rostyslav Hryniv Professor at Ukrainian Catholic University |
![]() Dmytro Fishman Assistant of Data Science at University of Tartu, Estonia |
![]() Andriy Gazin Data Visualization Specialist, Ukraine |
![]() Dr. Anastasios Noulas A Moore-Sloan Fellow at New York University Center for Data Science |
![]() Igor Koval PhD student at Pitié-Salpétrière Hospital, France |
![]() Liubomyr Bregman Senior Consultant specialized in Data Analysis at PwC Prague, Czech Republic |
![]() Habet Madoyan Doctor of Economics, lecturer at American University of Armenia |
![]() Dr. Manuel Gomez Rodriguez Tenure-track faculty at Max Planck Institute for Software Systems, Germany |
![]() Dr. Jozef Baruník Associate Professor at Charles University, Czech Republic |
![]() Dr. Tetiana Bogodorova Research Associate at Ukrainian Catholic University |
![]() Dr. Shinichi Shirakawa Lecturer at Yokohama National University, Japan |
![]() Oleksa Stepaniuk Data Analyst at Kyiv School of Economics, Ukraine |
![]() Dr. Tymofii Brik Assistant Professor at Kyiv School of Economics, Ukraine |
![]() Oleksii Pasichnyi Ph.D. candidate at KTH Royal Institute of Technology, Sweden |
![]() Serhii Havrylov Ph.D. student at University of Edinburgh, United Kingdom |
![]() Dr. Viktoriia Sharmanska Research Fellow at Imperial College London, United Kingdom |
![]() Dr. Novi Quadrianto Senior Lecturer at University of Sussex, United Kingdom |
![]() Adam Blascik Data scientist at PwC Czech Republic |
![]() Juan Pablo Figueroa Senior Data Scientist at N-iX, Ukraine |
![]() Dr. Julia Proskurnia Software Engineer at Google, Switzerland |
![]() Dr. Maciej Koch-Janusz Theoretical physicist at ETH Zurich, Switzerland |
![]() Oles Dobosevych Deputy Dean at Ukrainian Catholic University |
![]() Dr. Mykola Maksymenko Research Lead at SoftServe, Ukraine |
![]() Dr. Yurij Holovatch Head of the Laboratory at Institute for Condensed Matter Physics |
Participants’ projects
- Alzheimer’s disease prediction: Team 1
- Alzheimer’s disease prediction: Team 2
- Detecting person’s direction of interest: Team 1
- Detecting person’s direction of interest: Team 2
- Hyperparameter optimization
- Predicting collaboration in parliaments
- Pharmacy stores sales prediction
- Catch the money launderers!
- Self-driving-robot
- Prozorro risk prediction
- Facts extraction
- FPredicting the success of retail establishments in New York
- Semantic matching for healthcare statements
- Segmentation of challenging microscopy images
- A simple forecasting model for the US economy
- X FareForecasting
- Predicting the outcome of an NBA basketball game
Contacts
In case you have any questions, please contact us via- Email: lvcs@ucu.edu.ua