πŸ“… 2025-03-10 β€” Session: Conducted Educational Exercises and Course Evaluations

πŸ•’ 13:20–13:45
🏷️ Labels: Matplotlib, Python, Data Science, Education, Course Evaluation
πŸ“‚ Project: Teaching
⭐ Priority: MEDIUM

Session Goal

The session aimed to execute practical exercises in data science education and evaluate course content for improvements.

Key Activities

  1. Scientific Figure Creation with Matplotlib: Conducted an exercise to teach students how to create publication-quality scientific figures using Matplotlib and the law of Zipf.
  2. Exploratory Data Analysis (EDA) Report: Guided students through selecting an open dataset, documenting it, and performing an EDA using Python and Markdown, culminating in exporting the report to PDF and HTML.
  3. Data Narrative Exercise: Focused on storytelling with data, where participants chose a relevant topic and developed a presentation combining data analysis and storytelling.
  4. Course Evaluation in Data Science: Analyzed the structure and content of a data science course, highlighting strengths and areas for improvement.
  5. Probability and Statistics for Machine Learning Evaluation: Reviewed a teaching segment on Probability and Statistics, including simulations and practical exercises, with suggestions for enhancement.

Achievements

  • Successfully executed educational exercises that enhance students’ practical skills in data science and visualization.
  • Provided detailed evaluations of course content, offering insights into potential improvements.

Pending Tasks

  • Implement suggested improvements in the evaluated courses for future iterations.