Cursos en esta ruta
Python Essentials Guide
This guide teaches you Python from scratch, focused on what a backend developer actually needs: data types, control flow, functions, modules, error handling, working with files and JSON, and virtual environments. It's the foundation for the Backend Python Developer path.
21 lecciones
LLM Access Strategies Guide
Learn to choose the optimal LLM access strategy for any project — cloud APIs, local models, multi-provider aggregators, or serverless deployment — using a structured decision framework with quantitative trade-offs.
64 lecciones
Git & GitHub Guide
``` EN: "Master version control with Git and collaborative development with GitHub, from your first commit to production CI/CD pipelines." ES: "Domina el control de versiones con Git y el desarrollo colaborativo con GitHub, desde tu primer commit hasta pipelines de CI/CD en producción. Esta guía te lleva paso a paso por todo lo que necesitas para trabajar profesionalmente con Git: flujo local, branches, resolución de conflictos, Pull Requests, workflows de equipo, automatización con hooks y GitHub Actions, y recuperación de errores. Diseñada para developers de cualquier lenguaje que quieren dejar de tenerle miedo a Git y empezar a usarlo con confianza en equipos reales." ```
104 lecciones
Embeddings Deep Dive Guide
Master embeddings for production AI: implement semantic search from scratch with numpy, compare OpenAI vs open-source models, optimize with batch processing and caching, evaluate quality with precision@k and MRR, and build a complete production-ready semantic search engine.
64 lecciones
Vector Databases Fundamentals Guide
``` EN: Learn how vector databases store and retrieve embeddings for RAG systems — from architecture and indexing algorithms to hands-on ChromaDB implementation and production decision-making. ES: Aprende cómo funcionan las vector databases por dentro, por qué las necesitas para sistemas RAG y cómo elegir la correcta para tu proyecto. Esta guía te lleva desde los fundamentos (arquitectura, algoritmos de indexing, features esenciales) hasta implementación hands-on con ChromaDB y un proyecto integrador de RAG con 1,000+ documentos y API FastAPI. Al terminar, sabrás implementar storage y retrieval de vectores para producción — y tendrás criterio para decidir entre ChromaDB, Pinecone, Weaviate y Qdrant según tus requisitos reales. ```
67 lecciones
LangChain & LangGraph: From Chains to Agents
``` EN: Build production-ready AI agents and workflows with LangChain and LangGraph — from model integration and tool calling to multi-agent systems, memory, human-in-the-loop, and observability with LangSmith. ES: Aprende a construir agentes y workflows de AI listos para producción con LangChain y LangGraph. Esta guía te lleva desde conectar modelos y crear tools, hasta diseñar sistemas multi-agente con memoria persistente, supervisión humana y observabilidad completa. Ideal para developers que ya dominan Python y quieren construir aplicaciones de AI que van más allá de un simple chatbot — con control total sobre el flujo de ejecución, manejo de errores, y las mejores prácticas para llevar agentes a producción. ```
96 lecciones
Evaluation Frameworks Guide
``` EN: Master the evaluation of AI systems — from metrics for chat, RAG, and agents to LLM-as-judge, RAGAS, TruLens, and production evaluation pipelines. Learn to build golden datasets, implement domain-specific evaluation for chatbots, RAG pipelines, and AI agents, automate evaluation with calibrated LLM judges, and deploy continuous monitoring with CI/CD integration and regression detection. ES: Domina la evaluación de sistemas de AI — desde métricas para chat, RAG y agents hasta LLM-as-judge, RAGAS, TruLens y pipelines de evaluación en producción. Esta guía te enseña a construir golden datasets, implementar evaluación específica por dominio para chatbots, pipelines RAG y agentes de AI, automatizar la evaluación con LLM judges calibrados, y deployar monitoring continuo con integración CI/CD y detección de regresiones. Para AI Engineers que ya construyen sistemas y necesitan saber si realmente funcionan bien. ```
64 lecciones
Production Best Practices Guide
Master the engineering practices that separate AI prototypes from production systems: testing strategies for non-deterministic outputs, input/output guardrails, structured logging with cost tracking, clean architecture patterns for LLM applications, and reliability patterns including retry, circuit breakers, and fallback strategies.
64 lecciones
Docker Essentials Guide
Master Docker for AI applications: build optimized images, containerize FastAPI + LLM apps, orchestrate multi-service stacks with Docker Compose (API + ChromaDB + Redis), and apply production best practices including multi-stage builds, secrets management, and health checks. Your gateway to production deployment.
64 lecciones
Monitoring & Observability Guide
Master the observability of AI systems in production with OpenTelemetry, the industry standard for 2026. Learn to instrument LLM applications with traces for prompts, embeddings, and tool calls, build dashboards for latency and cost, design alerting strategies, implement AI-specific monitoring (prompt quality, token usage, model drift), and debug production issues like hallucinations and cost spikes. Integrates with LangSmith and monitoring backends.
64 lecciones
Security Deep Dive Guide
Secure your AI systems in production with the industry-standard OWASP LLM Top 10 framework. Master prompt injection defense (direct and indirect), enterprise-grade secrets management beyond .env (HashiCorp Vault, cloud KMS, rotation), input/output sanitization, PII protection, and AI-specific security testing. Designed for AI Engineers with deployed systems who need to harden them against AI-native threats. 8 modules, real breach case studies, and a fully secured AI system as your capstone project.
64 lecciones
System Design & Scaling Guide
Master architectural thinking for AI systems: scaling strategies, reliability patterns, integration patterns (webhooks, event-driven, MCP), real-world channels (Slack/Discord), and performance vs cost trade-offs. This synthesis guide connects everything you've learned—Docker, CI/CD, deployment, monitoring, cost optimization, security—and teaches you to DESIGN production-ready systems. Culminates with the complete architecture design for the Capstone: AI-Powered Knowledge Assistant with Agentic RAG and Slack/Discord integration.
64 lecciones