Developed and Evaluated Academic Data Exercises

2 min read

Developed and Evaluated Academic Data Exercises

  • Day: 2025-06-18
  • Time: 05:30 to 07:30
  • Project: Teaching
  • Workspace: WP 1: Strategic / Growth & Development
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Data Modeling, SQL, Machine Learning, Data Quality, Education

Description

Session Goal

The session aimed to develop and evaluate various academic exercises and exams focusing on data modeling, SQL pipelines, machine learning evaluation, and data quality.

Key Activities

  • Proposed a modeling exercise for a banking system, including an entity-relationship diagram (ERD) and normalization steps.
  • Detailed steps for creating a banking model, mapping to a relational model, and critically evaluating the design.
  • Discussed true/false questions for machine learning models focusing on F1 score and hyperparameter evaluation.
  • Proposed a regression exam using decision trees, addressing overfitting and underfitting.
  • Analyzed an ER diagram for academic management systems, including normalization and critical evaluation.
  • Developed SQL exercises for teaching data pipelines and aggregation patterns.
  • Structured exams for topics A, B, and C, including comparative evaluations and rubric creation.
  • Outlined data quality exercises using pandas for educational purposes, emphasizing analytical thinking.
  • Designed a four-month programming and data analysis course, combining in-person and virtual classes.

Achievements

  • Successfully structured and evaluated various academic exercises and exams.
  • Developed a comprehensive curriculum for a data analysis course.
  • Enhanced understanding of data modeling, SQL, machine learning, and data quality concepts.

Pending Tasks

  • Finalize the course structure and resources, including a canonical document and editable table for coordination.
  • Continue refining exam questions and evaluation rubrics.

Evidence

  • source_file=2025-06-18.sessions.jsonl, line_number=3, event_count=0, session_id=a47de87eb4e4e9d3475559376028b5f3adad0f8365e6f6ce25c4433ed43d72d1
  • event_ids: []

Graph View

Backlinks