Developed Data Science Exercise Catalog

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Developed Data Science Exercise Catalog

  • Day: 2025-03-10
  • Time: 04:30 to 06:00
  • Project: Teaching
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Data Science, Education, Exercises, Visualization, Statistics, Machine Learning

Description

Session Goal

The session aimed to develop a comprehensive catalog of practical exercises for advanced Data Science courses, focusing on [[data visualization]], exploratory analysis, and statistical concepts.

Key Activities

  • Compiled a list of 20 practical exercises aligned with advanced Data Science classes, emphasizing [[data visualization]] and exploratory analysis.
  • Proposed structuring exercises in a detailed format, potentially using interactive notebooks.
  • Provided feedback on a catalog of exercises for teaching Python and Pandas, suggesting improvements for course organization.
  • Created a collection of 15 rigorous exercises on probability, hypothesis testing, and regression for hard science students, including simulations and code examples.
  • Detailed a practical exercise on A/B testing, focusing on Type I and II errors in an e-commerce context.
  • Conducted an analysis of hypothesis testing for comparing proportions using a two-sample Z-test in Python.
  • Suggested advanced statistical topics to enrich a statistics course, such as simulations and dimensionality reduction.
  • Compiled a list of 20 exercises to help students master machine learning concepts through practical and theoretical approaches.

Achievements

  • Successfully compiled and structured a diverse set of exercises covering key areas in Data Science and Statistics.
  • Enhanced the educational content with practical examples and feedback for better engagement and understanding.

Pending Tasks

  • Finalize the structuring of exercises into interactive notebooks.
  • Incorporate feedback into the existing exercise catalog for Python and Pandas.
  • Develop detailed solutions and instructions for each exercise.

Evidence

  • source_file=2025-03-10.sessions.jsonl, line_number=0, event_count=0, session_id=bf67ff8a16f10aa3ce5a31645247e68b891e0bac9f94fd0a15a874d0120c7bd2
  • event_ids: []

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