📅 2023-08-02 — Session: Structured Algorithm Learning and Exercise Design
🕒 17:50–18:30
🏷️ Labels: Algorithms, Dynamic Programming, Greedy Algorithms, Education, Exercises
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to develop a structured approach to teaching and learning various algorithmic techniques, focusing on dynamic programming and greedy algorithms.
Key Activities
- Recursive Problem Formulation: Developed a recursive algorithm for optimal number selection from a matrix.
- Algorithm Exercises Overview: Planned exercises involving dynamic programming, backtracking, and greedy algorithms.
- Backtracking, Dynamic Programming, and Greedy Algorithms Overview: Reflected on key concepts and practical applications of these techniques.
- Exercise Mapping: Mapped exercises to algorithm concepts to enhance learning.
- Expanded Learning Sessions: Planned detailed educational sessions on dynamic programming and greedy algorithms.
- Session 2 Overview: Focused on dynamic programming with the ‘Terreno’ problem.
- Session 4 Overview: Introduced greedy algorithms with ‘Parejas de Baile’ exercise.
- Session 5 Breakdown: Focused on greedy algorithms and ethical considerations with ‘Escuela en Pandemia’ exercise.
Achievements
- Developed a comprehensive curriculum for algorithmic techniques.
- Created a series of exercises to reinforce learning.
- Mapped exercises to enhance educational outcomes.
Pending Tasks
- Conduct the planned educational sessions and evaluate their effectiveness.
- Develop additional exercises for deeper understanding of algorithmic concepts.