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This is a collection of the projects that I worked on while studying in the Yandex100 program. We worked in Python and SQL. Our projects had preprocessing, EDA, SDA, A/B testing, visualization, and much more
Project-based learning that provides data analysis skillset applicable to drive data-driven decisions to business, namely: data collection and analysis, design of model marketing scenarios , and executive communication of findings with Excel, Tableau, Google Analytics, and Data Studio.
The Shiny Chart Doctor is designed to bring the principles and techniques of effective data visualization, as championed by Alan Smith in his FT Chart Doctor column, to a wider audience.
The Challenges Repository is a collection of data analysis challenges, showcasing diverse methodologies and techniques. Each challenge folder contains an Excel file with the dataset and a README explaining the problem statement and analysis approach. Collaboration and feedback are encouraged to enhance the quality of the challenges.
Using machine learning technique of K-Nearest Neighbors and visualization tools, our group predicted credit score classification for bank customers based on 10+ features.