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IntermediocourseAcceso por bootcamp

Production Best Practices Guide

64

Lecciones

8

Módulos

🎓

Acceso por bootcamp

Lo que aprenderás

✓Set up professional testing infrastructure for LLM applications with pytest fixtures and markers
✓Write unit tests that mock LLM responses and validate prompts as behavioral contracts
✓Handle non-deterministic outputs with semantic similarity assertions and property-based testing
✓Implement guardrails pipelines with input sanitization, prompt injection defense, and output validation
✓Detect and redact PII in LLM inputs and outputs
✓Configure structured logging with correlation IDs, token tracking, and cost monitoring
✓Apply clean architecture patterns specific to AI applications (prompt/logic/infra separation)
✓Build reliability layers with retry, circuit breakers, rate limiting, and fallback strategies

¿Para quién es?

  • •AI Engineers who have built functional LLM applications and need to prepare them for production deployment
  • •Backend developers adding AI features who need professional testing and code quality standards
  • •Tech leads preparing teams to deploy AI systems with proper guardrails and observability
  • •Startups transitioning AI MVPs to production-ready products with reliability requirements
  • •Developers who want to differentiate themselves with professional AI engineering practices

Requisitos

  • •Python intermediate (OOP, decorators, type hints, Pydantic basics)
  • •Experience with REST APIs (FastAPI or similar)
  • •Basic LLM usage (OpenAI API or equivalent)
  • •Evaluation concepts from Guide #12 (metrics, golden datasets, quality measurement)
  • •Basic familiarity with pytest (running tests, simple assertions)

Contenido del curso

1Módulo 1: Testing Fundamentals para AI — Guía para el Creador8 lecciones
2Módulo 2: Unit Testing LLM Applications — Guía para el Creador8 lecciones
3Módulo 3: Integration Testing & Estrategias No-Determinísticas — Guía para el Creador8 lecciones
4Módulo 4: Guardrails — Input & Output Validation — Guía para el Creador8 lecciones
5Módulo 5: Structured Logging para AI Systems — Guía para el Creador8 lecciones
6Módulo 6: Code Quality Patterns para AI — Guía para el Creador8 lecciones
7Módulo 7: Reliability Patterns & Production Checklist — Guía para el Creador8 lecciones
8Módulo 8: Proyecto Integrador — Production-Ready AI System — Guía para el Creador8 lecciones
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