Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 1


[ 09/2019 – 06/2023 ]

Bachelor's in Applied Mathematics
Igor Sikorsky Kyiv Polytechnic Institute, IPT faculty

Field(s) of study: Mathematical methods of modeling, pattern recognition and computervision
Participated in several university projects, including developing a machine learning model
for data classification and clustering; computer vision system for object detection.

Skills obtained:

1. Data science:
    Confidence intervals and estimation for deviation, mean and distribution.
Probability estimation. Least squares method
    Kolmogorov-Smirnov, chi-squared, asymptotic theory for statistical
hypothesistest

2. Machine Learning:
   Data preprocessing, exploratory data analysis, data splitting, plotting
   Linear regression, XGboost (XGBRegressor)
   KNN classifier, MLP classifier, Random Forest classifier, C-Support vector
classification
   K-Means clustering

3. Computer vision:
    Spatial and frequency methods of image processing
    Color, morphological image processing
     Image segmentation
     Pattern recognition of numbers using tensorflow keras

4. SQL:  
    SQL db creation, insertion, Database normalization (Normal Forms)
    Advanced SQL (regular expressions, JOINS, UNION, Subqueries, WITH
expressions)
    SQL triggers, procedures, encryption

5. Relevant university programs:
    Probability Theory
    Mathematical Statistics
    Computational Complexity Theory

Introduction to Data Science in Python
Coursera

Mastered:
1. NumPy

2. python 're', 'lxml', 'bs4' libraries for text parsing

3. Pandas(df and series manipulations, merge, groupby, apply, etc.)

4. Data preparation skills