📅 2025-03-11 — Session: Conducted Various Data Science and Database Exercises
🕒 01:50–03:10
🏷️ Labels: Data Science, Database Modeling, SQL, Python, Teaching
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to execute a variety of practical exercises in data science and database modeling to enhance understanding and teaching capabilities.
Key Activities
- Conducted a comparison exercise between Pandas and SQL using Jupyter Notebook to illustrate syntax and performance differences.
- Executed a database modeling exercise with DBML, focusing on ER diagrams and SQL schema generation.
- Normalized a geographic dataset from the 2010 Argentina Census in BigQuery, including analysis, design, and evaluation.
- Compiled SQL and Python snippets for data transformation and visualization using Pandas and Seaborn.
- Developed a series of standardized exercises for data analysis and visualization.
Achievements
- Successfully executed and documented multiple exercises across data science and database design domains.
- Enhanced instructional materials for teaching database modeling and data analysis.
Pending Tasks
- Review and refine the exercises for clarity and effectiveness in teaching scenarios.