Completed a Data Analytics training program with hands-on projects, including: ● Analysis of product metrics. ● Building dashboards. ● User behavior research. ● Conducting A/B tests. ● Working with databases (ClickHouse, PostgreSQL). ● Writing SQL queries. ● Data visualization in Superset and Excel. Developed dashboards for retention, user activity, and action conversion rates.

During the training and practical projects, I developed strong skills in: ● Data collection and processing: confident in data cleaning, aggregation, and analysis using SQL and Python (Pandas). ● Working with databases: experienced in writing queries, joining tables, and building analytical datasets (PostgreSQL, MySQL). ● Data visualization: creating dashboards and charts in Yandex DataLens, Tableau, Matplotlib, Seaborn, and Plotly. ● A/B testing and statistics: conducting t-tests, z-tests, and Mann–Whitney tests to validate hypotheses and analyze results. ● ETL and BI: building data pipelines and creating reports for business analytics (Airflow, Git). ● Python development: working with NumPy, SciPy, and Scikit-learn for data analysis and modeling. ● Analytical thinking: solving real business cases, interpreting metrics, and preparing insights and recommendations.