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Fundamentals of Building AI Agents

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IntermediateCourse

Learn to enhance AI workflows with function calling and tool integration in LangChain. This course covers the fundamentals of function calling, tool creation, and chaining techniques to streamline interactions with language models. You’ll start by building AI agents that dynamically select and execute tools, then explore chaining methods using LangChain Expression Language (LCEL) to link prompts, models, and outputs. Finally, you'll implement manual tool-calling pipelines for greater control, ensuring accuracy and reliability in high-stakes applications.

4.6 (146 Reviews)

Language

  • English

Topic

  • Artificial Intelligence

Industries

  • Information Technology

Enrollment Count

  • 50.44K

Skills You Will Learn

  • AI Agent, LangChain, LangGraph, LLM Application Developmen, Tool Calling

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 3 weeks/2 hours

Platform

  • Coursera

Last Update

  • March 17, 2026
About this Course
Are you ready to build AI that thinks, acts, and gets things done? In this course, you’ll learn how to design agents that go beyond language generation to reason, take action, and tackle real-world tasks using tools and data.  
 
During the course, you'll explore the foundations of function calling, tool orchestration, and chaining with LangChain. You’ll discover how to extend the capabilities of Large Language Models (LLMs) by connecting them with calculators, code, and external data sources. You'll learn how LLMs trigger tool use through LangChain Expression Language (LCEL) and look at manual tool calling for greater control and accuracy. Plus, you’ll explore built-in agents that can analyze data, create visualizations, and run SQL queries using natural language.  
 
To get the most from this course, we recommend that you have Python programming skills, a basic understanding of LangChain, and familiarity with core AI concepts.  
 
Whether you're building a chatbot or a smart assistant, if you’re looking to build the skills to create dynamic, intelligent, and goal-oriented AI systems, enroll today!  


Learning Objectives

  • Develop AI agents that can reason and perform tasks independently  
  • Implement tool calling and chaining to create structured AI workflows 
  • Utilize built-in LangChain agents to analyze data, generate visualizations, and execute database queries  
  • Apply best practices in prompt engineering and tool calling to enhance AI agent performance
 

Course Syllabus


Module 1: Foundations of Tool Calling and Chaining

  • Lesson 0: Welcome
  • Lesson 1: Introduction to AI Agents
  • Lesson 2:  Getting Started with Tool Calling 
  • Lesson 3: Building and Orchestrating Tools
  • Lesson 4: Module Summary and Evaluation  

Module 2:  LCEL and Manual Tool Calling in LangChain  

  • Lesson 1: Introduction to Chaining and LCEL Basics
  • Lesson 2: Manual Tool Calling Basics
  • Lesson 3: Parsing and Validating Tool Calls  
  • Lesson 4: Module Summary and Evaluation  

Module 3: Using Built-in Agents in LangChain 

  • Lesson 1: Natural Language Data Visualization 
  • Lesson 2: Conversational Database Access
  • Lesson 3: Module Summary and Evaluation
  • Lesson 4: Course Wrap-Up