The main purpose of studying Data Science Programming is to develop the capability to transform raw and unstructured data into meaningful and actionable insights.

Through programming, students learn how to systematically organize data, automate analytical procedures, and produce results that support evidence-based decision making.

We study Data Science Programming because modern industries increasingly rely on data for strategic planning, prediction, and performance evaluation.

Programming skills allow individuals to conduct exploratory data analysis (EDA), build predictive models, and communicate analytical findings effectively.

To become proficient, it is essential to master programming languages such as Python or R, as they form the foundation for data manipulation, analysis, and modeling.

Additional tools include professional code editors like Visual Studio Code, statistical libraries, data visualization tools, database systems such as SQL, and version control platforms like Git.

In terms of domain knowledge, I am interested in business analytics within the digital gaming industry. Specifically, I am curious about how companies such as SNK, Moonton, and SEGA analyze user behavior, improve player engagement, and develop data-driven strategies to support business growth and market expansion.

For example, these companies analyze player retention rates to understand why users stop playing after a certain period. They also examine in-game purchase patterns to optimize monetization strategies and evaluate marketing effectiveness to identify regions with high growth potential.

I aim to deepen my understanding of user retention, monetization strategies, and strategic decision-making in digital platforms.