📅 2024-10-29 — Session: Strategic Planning for Data Science and Electoral Campaigns
🕒 15:20–15:40
🏷️ Labels: Data Science, Electoral Campaign, Curriculum Development, Team Management, Automation
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal:
The session aimed to explore strategic planning within the Data Science educational track and electoral campaigns, focusing on institutional challenges, curriculum development, and campaign strategies.
Key Activities:
- Institutional Challenges: Discussed leadership dynamics and communication strategies to enhance collaboration within the Data Science track at the university.
- PhD Program Proposal: Outlined feasibility and considerations for establishing a PhD program in Data Science, including curriculum and research needs.
- Screening Agent: Prepared an automation agent for organizing AI session knowledge, focusing on semantic memory.
- Academic and Political Challenges: Summarized discussions on challenges and proposed blog content structure.
- Thesis Development: Reviewed Matías Iglesias’s research focus, thesis proposals, and publication strategies.
- Relationship Mapping Project: Outlined a data pipeline for classmate relationship mapping based on shared courses.
- Curriculum Analysis: Analyzed specialization paths and course categorization for Data Science students.
- Electoral Campaigns: Developed strategies for voter mobilization and narrative development for the LCD.
- Team Role Structuring: Proposed role structures for campaign teams to optimize mobilization and communication.
Achievements:
- Developed comprehensive strategies for both educational and electoral contexts.
- Initiated automation for knowledge management.
- Proposed a structured approach to curriculum and thesis development.
Pending Tasks:
- Further refinement of the PhD program proposal.
- Implementation of the screening agent for knowledge management.
- Execution of the electoral campaign strategies and role assignments.