Unit 6 — Integration Project
Overview
End-to-end scientific project pipeline: from proposal to production deployment with CI/CD.
Topics
- Scientific project proposal (structured JSON)
- Technical implementation plan
- Multi-agent pipeline integration (Units 1–5)
- FastAPI deployment with Docker
- Monitoring: Prometheus + Grafana
- Final scientific report generation
Key Technologies
- FastAPI — REST API for serving models
- Docker — Containerized deployment
- Prometheus / Grafana — Observability
- GitHub Actions — CI/CD
Project Structure
mi_proyecto_api/
├── main.py # FastAPI application
├── Dockerfile # Production container
├── requirements.txt
└── tests/
Learning Outcomes
- Design a complete scientific AI project from scratch
- Deploy a FastAPI endpoint with a trained model
- Implement monitoring and observability
- Integrate all course components in a single pipeline
- Write a publication-ready technical report