Fundamentals of Building AI Agents
By External Provider
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 tool calling 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!
What you will learn
- 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