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- Career-focused from day one: get job-ready in 24 weeks and hired in 120 days
- The only bootcamp that doesn't end at graduation, unlimited lifetime mentorship included
- Flexible financing available: pay as low as $349/mo or $0 upfront with our Income Share Agreement
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Ingeniero de IA
- Mentoría ilimitada de por vida con ingenieros senior, incluso después de graduarte
- Paga en 10, 12 o 18 cuotas mensuales sin dejar tu trabajo actual
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Te enviamos el programa completo con plan de estudios, opciones de financiación y más. Solo toma 2 minutos.
AI Native Full Stack — Program Modules
Build real AI-powered systems from day one. This curriculum is organized around two tracks — Core AI and Agents, and Infrastructure for AI — plus a capstone that integrates everything into a fully transformed, deployed company. Supported by complementary foundations in modern development tools and practices throughout.
Core AI and Agents
Personal Assistants with OpenClaw
- Configure an open-source AI agent as a personal assistant
- Assign tasks and integrate external applications with the agent
Projects:
Deploy and configure a self-hosted AI assistant — yours, under your control, without relying on external vendors.
Core AI and Agents
Advanced Personal Assistants with OpenClaw
- Identify scenarios where an agent solves real business problems
- Develop custom skills for OpenClaw
- Implement contextual memory (episodic, semantic, procedural)
- Advanced configuration and extension of the agent
Projects:
Take your basic assistant agent to a productive tool with real autonomy in business contexts.
Core AI and Agents
Working with AI Coding Agents
- Build memory banks and context rules from an existing codebase
- Write executable specifications for agents (agent specs)
- Synthesize reusable skills so agents act with precision
Projects:
Build memory banks and context rules that turn a coding agent into a collaborator that understands your codebase.
Core AI and Agents
LLMs, Training & RAG
- Prepare data and select models for training
- Implement RAG techniques on proprietary knowledge bases
- Work with vector databases
- Evaluate, debug, and integrate models in production
Projects:
Implement RAG so your agent answers with proprietary, up-to-date knowledge.
Core AI and Agents
Agentic Engineering
- Build agents with tool calling (real function calls)
- Implement guardrails as a security and control mechanism
- Provide tools to the agent via CLIs optimized for AI
- Extend agent capabilities with the Model Context Protocol (MCP)
Projects:
Build agents that call tools, access external systems via MCPs and CLIs, and operate with persistent memory.
Core AI and Agents
Agentic Workflows
- Design multi-agent systems with routing and arbitration
- Implement shared memory across agents
- Deploy agentic workflows with serverless and durable functions
Projects:
Design systems where multiple agents collaborate, distribute tasks, and run autonomously at scale.
Infrastructure for AI
Backend Development with Coding Agents
- Design backend architectures for AI-powered solutions
- Create agent loops integrating LLMs with APIs
- Implement lightweight storage and CSV data processing
- Build and expose REST APIs for frontends and agents
Projects:
Build robust APIs with FastAPI, implement agent loops in Python, and design backend architectures for AI use cases.
Infrastructure for AI
Workflow Automations
- Model business logic with workflow diagrams
- Implement basic and advanced flows in n8n
- Integrate LLMs and external apps in automations
- Deploy maintainable workflows with error handling
Projects:
Build AI-powered business automations in n8n that run autonomously without manual intervention.
Infrastructure for AI
Data Pipelines
- Manipulate and prepare datasets with Python
- Build data pipelines from the application to analysis systems
Projects:
Build pipelines that take raw data, transform it, and leave it ready to feed models, reports, or agents.
Infrastructure for AI
Telemetry
- Optimize storage for reporting and data integrity
- Identify data collection opportunities in real scenarios
- Collect telemetry and user context from the application
- Build reports from telemetry data
Projects:
Instrument applications to collect behavioral data and make decisions based on real evidence.
Infrastructure for AI
Asynchronous Processing and Offloading
- Implement background processing for costly tasks
- Manage process queues with workers
- Use queues to delegate work between agents and services
Projects:
Implement background processing and queue systems that let agents delegate heavy work without blocking users.
Infrastructure for AI
Real-Time
- Build support chats with LLMs in real time
- Implement response streaming with generators (yield)
- Integrate webhooks and pub/sub in AI applications
Projects:
Implement real-time communication between users and language models using streaming, WebSockets, and event-driven architectures.
Infrastructure for AI
Web Application Authentication
- Implement authentication and route restrictions in FastAPI
- Build complete authentication flows (login, tokens, sessions)
Projects:
Implement secure authentication in FastAPI and build complete login flows that define what each user — and agent — can do.
Infrastructure for AI
Error Handling, Debugging and Testing
- Understand and manage runtime errors with flow control
- Develop test suites for robust applications
Projects:
Verify AI-generated code with controlled error handling and test suites that validate expected behavior.
Infrastructure for AI
Cybersecurity in AI Applications
- Identify and fix OWASP Top 10 vulnerabilities in web applications
- Implement security practices specific to AI integrations
- Use LLMs as a cybersecurity auditing tool
Projects:
Identify critical vulnerabilities in AI applications and implement safe practices in model integration.
Capstone
AI-Transformed Company
- AI-generated frontend
- API with full authentication
- Telemetry and reporting pipeline
- Agent-generated automated workflows
- RAG knowledge layer
- Agents with tool calling
- Real-time communication
Projects:
Integrate everything you have learned into a working, deployed system — a full transformation of a company through AI.
The Bootcamp That Doesn't End When You Graduate
Most bootcamps disappear after demo day. 4Geeks stays with you from your first line of code to your first offer letter and beyond.
Career support built for the AI job market
Learn faster with an AI tutor that knows where you're stuck
Unlimited 1:1 mentorship for life, not just while enrolled
Career support built for the AI job market
- 1:1 coaching focused on landing AI engineering roles specifically
- Resume and portfolio optimized to pass AI-based recruiter screening
- Mock technical and behavioral interviews with real feedback
- Lifelong career support, not just until graduation
Your Certificate. Your Salary Leverage.
Graduate with the skills, credentials, and professional profile employers are actively hiring for right now.
Certificate
of Achievement
This certificate is presented to
Pedro Fuentes Escaloso de los Lobos
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