Claude Code para Vibe Coding

Resumen

This program equips developers, engineers, and technical professionals with the practical skills needed to design, manage, and deploy AI-driven software development workflows using terminal-based autonomous agents. Designed for modern AI-first engineering environments, the course emphasizes hands-on learning with Claude Code, structured instruction design, and Model Context Protocol (MCP) to help learners build scalable, production-ready systems efficiently and reliably.

You will begin by exploring the foundations of terminal-based AI agents and autonomous coding workflows, gaining clarity on how these systems interpret instructions, execute commands, and interact with development environments. This includes understanding the differences between IDE assistants and terminal agents, how instruction quality impacts execution outcomes, and how developers can shift from manual coding to orchestrating AI-driven tasks.

You will also gain hands-on experience setting up Claude Code and running your first commands to establish a strong operational baseline. Building on this foundation, the course introduces advanced task delegation and autonomous feature development.

You will learn how to structure clear, multi-step instructions that enable AI agents to build complete features, enhance applications, and handle complex workflows. The curriculum then expands into Model Context Protocol (MCP), where you will explore how AI systems integrate with external tools, APIs, and data sources.

Through practical exercises, you will design and implement custom MCP servers, enabling AI agents to interact with real-world systems and extend beyond isolated code generation. Next, the program focuses on integrating autonomous agents into professional development and DevOps workflows.

You will gain hands-on experience using Claude Code for automated testing, debugging, and validation, while learning how to incorporate AI into CI/CD pipelines and collaborative engineering processes. The course demonstrates how to maintain control, visibility, and reliability when working with autonomous systems in production environments.

The curriculum then emphasizes quality assurance, security, and best practices for AI-assisted development. You will learn how to validate AI-generated outputs, perform structured code reviews, apply security scanning techniques, and ensure that AI-driven workflows meet professional engineering standards.

The course reinforces the importance of balancing automation with oversight to achieve both speed and reliability in production systems. Finally, the course culminates in a comprehensive capstone experience where you design, build, and deploy a production-ready application using terminal-based AI agents.

You will apply autonomous task delegation, MCP integration, testing strategies, and deployment workflows in an end-to-end project that reflects real-world AI-first software engineering practices. By the end of this course, you will be able to:

Use terminal-based AI agents to execute and automate software development tasks Design structured instructions for reliable autonomous feature development Integrate external tools, APIs, and data sources using Model Context Protocol (MCP) Build and deploy custom MCP servers to extend AI capabilities Apply automated testing, debugging, and validation to AI-generated code Integrate AI agents into CI/CD and DevOps workflows Ensure security, reliability, and governance in AI-assisted development systems Design and implement end-to-end AI-driven production applications This course is designed for:

Software developers transitioning to AI-driven and autonomous workflows DevOps engineers looking to automate development and deployment pipelines Engineering leads adopting AI-first development practices Computer science students preparing for next-generation development environments Technical professionals exploring AI agent frameworks and integrations Developers seeking to move beyond IDE assistants into autonomous execution systems Join us to master terminal-based AI agents, autonomous development workflows, and MCP integration, and gain the skills required to build reliable, scalable, and production-ready systems in the era of AI-driven software engineering.

Programa

• Introducción a los Agentes de IA Basados en Terminal
Construya una base sólida en el desarrollo asistido por IA basado en terminal al comprender cómo operan los agentes de codificación autónomos fuera de los entornos tradicionales de IDE. Explore las diferencias entre los agentes de terminal y los asistentes de IDE, y aprenda cómo los sistemas de IA ejecutan comandos, interpretan instrucciones e interactúan con su entorno de desarrollo. Adquiera experiencia práctica instalando y configurando Claude Code, ejecutando sus primeros comandos y entendiendo los flujos de trabajo fundamentales que permiten a los desarrolladores pasar de la codificación manual a la ejecución impulsada por instrucciones.
• Código Claude Avanzado e Integración MCP
Avance sus habilidades en el desarrollo impulsado por IA aprendiendo cómo delegar tareas complejas y de múltiples pasos a Claude Code usando instrucciones estructuradas. Explore cómo los agentes autónomos pueden construir características completas, mejorar aplicaciones e integrarse con sistemas externos. Comprenda el Protocolo de Contexto de Modelo (MCP), cómo extiende las capacidades de la IA a través de herramientas y APIs, y cómo diseñar y desplegar servidores MCP personalizados. Desarrolle la habilidad de orquestar flujos de trabajo inteligentes que combinen el razonamiento de IA con datos y servicios del mundo real.
• Pruebas y Aseguramiento de Calidad
Fortalezca su capacidad para desplegar sistemas asistidos por IA en producción enfocándose en pruebas, validación y fiabilidad operativa. Aprenda cómo evaluar y refinar código generado por IA mediante pruebas automatizadas y flujos de trabajo de depuración. Explore consideraciones de seguridad, prácticas de revisión de código e integración CI/CD para entornos de desarrollo asistidos por IA. Aplique su conocimiento en un proyecto final, donde construirá, probará y desplegará una aplicación lista para producción utilizando agentes de IA basados en terminal y mejores prácticas para un desarrollo escalable y seguro.
• Cierre del Curso
Este módulo está diseñado para evaluar a un individuo sobre los diversos conceptos y enseñanzas cubiertos en este curso. Evalúe su conocimiento con un cuestionario integral calificado.

Impartido por

Edureka

Materias

Artificial Intelligence