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)
  • Physicist’s approach to complex systems: search for fundamental laws by data analysis
• General courses (July 17-21)
  • Statistical Inference
  • Introduction to Machine Learning
  • Data Visualization
  • R Workshop
• 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)
  • Machine Learning and Physics

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