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CI/CD for AI Systems Guide

64

Lessons

8

Modules

🎓

Bootcamp access

Lo que aprenderás

✓Set up GitHub Actions workflows for AI projects from scratch
✓Automate pytest execution with matrix testing and dependency caching
✓Implement AI-specific CI checks: prompt regression testing and cost estimation
✓Manage secrets and environment variables securely in pipelines
✓Build and push Docker images automatically with layer caching
✓Create deployment pipelines with staging, approval gates, and production
✓Implement rollback strategies for failed deployments
✓Build production-grade pipelines with notifications and monitoring

¿Para quién es?

  • •AI Engineers who deploy manually and want to automate their delivery pipeline
  • •Teams that need consistent, automated testing and deployment for AI applications
  • •Developers who have Docker containers ready and need CI/CD to automate the flow
  • •Tech leads establishing DevOps practices for AI teams
  • •Anyone in the AI Engineering Path ready to automate their production workflow

Requisitos

  • •Git & GitHub proficiency (Guide #4)
  • •Docker fundamentals: Dockerfiles, Docker Compose (Guide #15)
  • •Testing basics: pytest, unit tests (Guide #13)
  • •Python intermediate
  • •No prior CI/CD experience required

Course content

1Módulo 1: Introducción a CI/CD y GitHub Actions — Guía para el Creador8 lessons
2Módulo 2: Testing Automatizado en CI — Guía para el Creador8 lessons
3Módulo 3: AI-Specific CI Checks — Guía para el Creador8 lessons
4Módulo 4: Secrets y Environment Management — Guía para el Creador8 lessons
5Módulo 5: Docker en CI/CD — Guía para el Creador8 lessons
6Módulo 6: Deployment Pipelines — Guía para el Creador8 lessons
7Módulo 7: Monitoring, Notifications y Advanced Patterns — Guía para el Creador8 lessons
8Módulo 8: Proyecto Integrador — Production AI Pipeline — Guía para el Creador8 lessons
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