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Curso gratuito English Certificado verificado Beginner #ai #machine learning #chatgpt #automation #building #agents #langchain #professionals

Building AI Agents with LangChain

In this course, you’ll learn how to build practical AI agents with LangChain, step by step. You’ll start with the basics of LLM apps, then move through prompts, tools, memory, retrieval, and agent workflows, ending with deployment and safety.

5.0 (3 valoraciones)
106 estudiantes inscritos
564 visualizaciones
30 lessons
~15 min en total
A tu ritmo, acceso de por vida

¿De qué trata este curso?

This beginner-friendly course helps working professionals learn how to design, build, and evaluate practical AI agents with LangChain. Starting from the fundamentals of LLM applications, you will progress through prompts, chains, tools, memory, retrieval, and agent workflows, then finish with deployment, safety, and best practices. Each module begins with a short introduction, uses real-world examples, and each lesson ends with practical exercises you can complete in 5-15 minutes. The course is hands-on, clear, and focused on building useful solutions step by step.

¿Cuáles son los datos clave de este curso?

Precio Gratis
Certificado Certificado verificado
Duración 15 min
Lecciones 30
Idioma English
Nivel Beginner
Examen A tu ritmo, acceso de por vida

Programa

6 modules · 30 lessons

1
Module 1: Getting Started with LangChain and AI Agents
5 lessons
  • What AI Agents Are and Where LangChain Fits
  • Core Concepts: Prompts, Models, Chains, and Tools
  • Setting Up Your Development Environment
  • Your First LangChain Application
  • How to Think Like a Builder: Problem, User, Output
2
Module 2: Prompting and Chain Design
5 lessons
  • Writing Clear Prompts for Reliable Results
  • Few-Shot Prompting and Examples
  • Structured Outputs and Formatting
  • Building Simple Chains
  • Testing and Improving Prompt Chains
3
Module 3: Memory and Conversation Management
5 lessons
  • Why Memory Matters in AI Agents
  • Types of Memory in LangChain
  • Designing Useful Conversation Flows
  • Preventing Memory Problems and Drift
  • Practical Memory Design for Business Agents
4
Module 4: Tools, Functions, and External Actions
5 lessons
  • What Tools Do in an AI Agent
  • Creating and Describing Tools Clearly
  • Calling Functions and Handling Results
  • Real-World Tool Examples
  • Safe Tool Use and Human Oversight
5
Module 5: Retrieval, Knowledge, and Grounded Answers
5 lessons
  • Why Retrieval Improves AI Answers
  • Working with Documents and Text Sources
  • Building a Simple Retrieval Workflow
  • Answering with Citations and Traceability
  • When Retrieval Fails and How to Improve It
6
Module 6: Building, Evaluating, and Deploying AI Agents
5 lessons
  • Planning a Complete Agent Solution
  • Testing Agent Behavior and Quality
  • Improving Reliability with Guardrails
  • Deploying for Real Users
  • Capstone: Design Your First Useful AI Agent

Certificado de finalización

Al terminar este curso desbloquearás un certificado verificado — descargable en PDF, con número único y enlace de verificación pública.

Cada certificado tiene un enlace verificable único y un código QR.

Preguntas frecuentes

Is this course free to start?

Yes. You can start learning this course for free.

Who is this course for?

This course is designed for learners who want practical, job-relevant skills and a structured path from basics to application.

Do I need prior experience?

No prior experience is required unless specific prerequisites are listed in the course requirements section.

How long does this course take?

The estimated total study time for this course is 15 min.

How does the certificate work?

Tras finalizar este curso podrás descargar un certificado verificado con un número único y enlace público de verificación.

Opiniones de los estudiantes

5.0
3 valoraciones
5
3
4
0
3
0
2
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1
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J
James W. Verificado · 16 may. 2026

Finally got chains vs agents.

J
Jessica L. Verificado · 6 ene. 2026

Tools made sense

The part on tools and memory clicked for me, especially how they fit into a LangChain agent workflow. It felt practical right away.

R
Rachel T. Verificado · 20 ago. 2025

Clear on retrieval

I liked the retrieval module most. The examples made it easy to see how an agent can use external context instead of just guessing.

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