πŸ“… 2023-06-09 β€” Session: Developed comprehensive course outline for Data Mining

πŸ•’ 10:10–10:30
🏷️ Labels: Data Mining, Economics, Finance, Course Design, Predictive Modeling
πŸ“‚ Project: Teaching
⭐ Priority: MEDIUM

Session Goal: The goal of this session was to develop a comprehensive and detailed course outline for a course titled β€˜Data Mining in Economics and Finance’. This course aims to equip students with the skills to apply data mining techniques specifically in the economic and financial sectors.

Key Activities:

  • Reviewed and outlined the course content distribution over 25 sessions, focusing on data mining, predictive modeling, time series analysis, and practical case studies.
  • Developed a revised course outline detailing modules covering various data mining techniques, applications, and ethical considerations.
  • Enhanced the course outline by integrating economics-focused topics and applications, including predictive modeling, time series analysis, and sentiment analysis.
  • Expanded the curriculum to include finance-related topics such as fraud detection and algorithmic trading.

Achievements:

  • Successfully created a comprehensive 64-hour course outline covering key topics such as data preprocessing, supervised and unsupervised learning algorithms, and ethical considerations.
  • Integrated advanced techniques and applications into the course structure, ensuring a robust educational framework.

Pending Tasks:

  • Finalize the detailed syllabus for each session, including specific learning objectives and assessment methods.