III Lviv Data Science Summer School 2018
Lviv Data Science Summer School is an educational initiative of the Faculty of Applied Sciences of the Ukrainian Catholic University. The Summer School participants – undergraduates, Ph.D. students, young professionals – study state-of-the-art methods and tools of Data Science, Machine Learning, Business Analytics. The school is oriented towards the basic level of participants’ knowledge.
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 |
![]() Dmytro Fishman Assistant of Data Science |
![]() Andriy Gazin Data Visualization Specialist, Ukraine |
![]() Dr. Anastasios Noulas A Moore-Sloan Fellow |
![]() Igor Koval PhD student |
![]() Liubomyr Bregman Senior Consultant specialized in Data Analysis |
![]() Habet Madoyan Doctor of Economics, lecturer |
![]() Dr. Manuel Gomez Rodriguez Tenure-track faculty |
![]() Dr. Jozef Baruník Associate Professor |
![]() Dr. Tetiana Bogodorova Research Associate |
![]() Dr. Shinichi Shirakawa Lecturer |
![]() Oleksa Stepaniuk Data Analyst |
![]() Dr. Tymofii Brik Assistant Professor |
![]() Oleksii Pasichnyi Ph.D. candidate |
![]() Serhii Havrylov Ph.D. student |
![]() Dr. Viktoriia Sharmanska Research Fellow |
![]() Dr. Novi Quadrianto Senior Lecturer |
![]() Adam Blascik Data scientist |
![]() Juan Pablo Figueroa Senior Data Scientist |
![]() Dr. Julia Proskurnia Software Engineer |
![]() Dr. Maciej Koch-Janusz Theoretical physicist |
![]() Oles Dobosevych Deputy Dean |
![]() Dr. Mykola Maksymenko Research Lead |
![]() Dr. Yurij Holovatch Head of the Laboratory |
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: [email protected]