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
AI Fundamentals Guide
Build a solid conceptual foundation in Artificial Intelligence — from ML basics and neural networks to Transformers, LLMs, and the modern AI API ecosystem — designed specifically for developers entering AI Engineering.
56 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
Python + REST APIs for AI
Master Python for consuming and exposing AI APIs professionally: OOP, async/await, HTTP fundamentals, streaming SSE, error handling, rate limiting, cost optimization, and a production-ready Flask AI Gateway that integrates everything.
80 lecciones
Git & GitHub Guide
Master version control with Git and collaborative development with GitHub, from your first commit to production CI/CD pipelines. This guide walks you step by step through everything you need to work professionally with Git: local workflow, branches, conflict resolution, Pull Requests, team workflows, automation with hooks and GitHub Actions, and error recovery. Built for developers of any language who want to stop fearing Git and start using it with confidence on real teams.
104 lecciones
AI Semantics Guide
Understand how vectors, vector spaces, similarity metrics and semantic search work conceptually — the foundational knowledge that makes embeddings, vector databases and RAG possible. A rigorous yet accessible guide with zero math prerequisites and zero code.
56 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
Learn how vector databases work under the hood, why you need them for RAG systems, and how to choose the right one for your project. This guide takes you from the fundamentals (architecture, indexing algorithms, essential features) to a hands-on implementation with ChromaDB and an integrative RAG project with 1,000+ documents and a FastAPI API. By the end, you will know how to implement vector storage and retrieval for production — and you will have the judgment to decide between ChromaDB, Pinecone, Weaviate, and Qdrant based on your real requirements.
67 lecciones
Advanced RAG Techniques Guide
Master advanced Retrieval-Augmented Generation patterns for production AI systems: chunking strategies, query optimization, re-ranking, hybrid search, metadata filtering, Pinecone deployment, and automated evaluation with RAGAS.
64 lecciones
LangChain & LangGraph: From Chains to Agents
Learn to build production-ready AI agents and workflows with LangChain and LangGraph. This guide takes you from connecting models and creating tools, to designing multi-agent systems with persistent memory, human-in-the-loop supervision, and full observability. Ideal for developers who already know Python and want to build AI applications that go beyond a simple chatbot — with full control over the execution flow, error handling, and the best practices for taking agents to production.
96 lecciones
Advanced Prompt Engineering Guide
Master the prompt engineering techniques that separate casual LLM users from production AI engineers: zero-shot and few-shot patterns, Chain-of-Thought reasoning, ReAct, Self-Consistency, prompt composition, systematic evaluation, and production prompt management with versioning, caching, and cost optimization.
64 lecciones
Building AI Agents Guide
Master the complete lifecycle of building AI agents — from tool calling and function calling patterns to state machines with LangGraph, MCP integration, multi-agent orchestration, and production deployment. Includes testing strategies, evaluation frameworks, and a comparison with Pydantic AI.
80 lecciones
Evaluation Frameworks Guide
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.
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
AI Multimodal Guide
Master multimodal AI: vision, audio, documents, and image generation. From GPT-4 Vision and Claude 3 to Whisper transcription, DALL-E, multimodal RAG, and document analysis. Build a complete multimodal document analyzer.
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
CI/CD for AI Systems Guide
Automate the delivery cycle of AI systems with GitHub Actions: run tests, prompt regression checks, and cost estimation in CI; build and push Docker images; deploy to staging and production with approval gates and rollback strategies. Everything AI engineers need to go from manual deploys to automated pipelines.
64 lecciones
Deployment & Cloud Infrastructure Guide
Master deployment strategies for AI systems: understand when to use Local, Serverless, Managed or Self-hosted; learn AWS (S3, Lambda, SageMaker basics) with LocalStack at zero cost; evaluate modern alternatives (Render, Railway, Fly.io); and build a complete decision matrix to choose the right deployment strategy. From Docker containers to production-deployed AI systems.
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
Cost Optimization & Caching Guide
Master cost reduction for AI systems: understand cost drivers (tokens, API calls, embeddings), implement Redis caching and semantic caching (similar queries = cached responses using embeddings), apply prompt optimization and model selection strategies, and build a system that achieves 50-80% cost reduction with real numbers. The only guide in Spanish that covers semantic caching hands-on.
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
AI Ethics & Compliance Guide
Learn AI ethics and compliance: bias detection, fairness metrics, the EU AI Act, and GDPR applied to AI systems. Close this AI Engineering ecosystem with the responsibility framework every AI Engineer needs. Master bias detection and fairness metrics, navigate the EU AI Act (risk categories, high-risk requirements, compliance timelines), apply GDPR to AI systems (right to explanation, consent, data minimization), and build a reusable ethics checklist. This guide transforms your technical skills into responsible AI practice with actionable deliverables.
64 lecciones