Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 0

- 2nd place at SPF ML 2023 Hackhathon run by KNU
- 2nd place in the competition of team projects at the DES2023 Winter School run by LNU
- INT20H 2023 Hackaton in Data Science (participant in final round)

Courses:
- Data Science Fundamentals (DataRoot Labs)
- Python Online Marathon (Softserve)
- Data Engineering and Security School 2023 (LNU)
- Wildau-Kharkiv IT Bridge (2022)
I finished 3 courses - Probability & Statistics, Data Mining and Programming for Data Analysis.
I am a 3 rd year student of computer engineering in Oles Honchar Dnipro National university and Intern Data Scientist. 
A list of projects and tasks that I have had experience with:
- Django web-application for searching by country legacy status of cryptocurrency
- Object detection system for video / image sequences from drones
- Sentiment analysis of comments in YouTube using LSTM
- U-net, YOLOv3 models implemented from scratch in PyTorch for image detection and classification
- Web-scrapping using bs4 python
- Data extraction using Google Maps API, Folium and GeoPandas (locations of shops in Ukraine where you currently can pay with crypto)
- Patients classification by diagnosis using KNN (university course)
- Regression tasks. For example, stroke prediction using Kaggle dataset.
- Correlation analysis of events and user properties in taxi ordering app (hackaton task for qualifying round)
- Binary and Multi-class classification in Pytorch
- Data visualization using Altair, Seaborn and Matplotlib


Technology stack:
	Programming languages - Python, C++
	Libraries for data analysis and visualization, machine learning, deep learning - NumPy, 	SciPy, 	Pandas, GeoPandas, Folium, Seaborn, Altair, Scikit-learn, XGBoost, Pytorch
	Frameworks: Flask, Django.
	Database: RDBMS, PostgreSQL
	Deployment tools: Docker, Git/Github