Free Download Build AI Agents with LangChain Tool Calling EssentialsPublished 1/2026
Created by Dilip Kumar P
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner |
Genre: eLearning |
Language: English |
Duration: 117 Lectures ( 4h 3m ) |
Size: 1.23 GB
Understand how AI agents reason, decide, and use tools within a controlled execution loop
Distinguish clearly between built-in tools and custom tools and know when to use each
Design and implement tool calling using LangChain with correct agent mental models
Avoid common mistakes in tool usage and think like an AI agent designer in real projects
RequirementsBasic familiarity with Python syntax is helpful but not mandatory
No prior experience with LangChain or AI agents is required
Curiosity to understand how modern AI systems actually work is enough
DescriptionBuild AI Agents with LangChain: Tool Calling EssentialsModern AI systems are no longer just about generating text. They are about making decisions, using tools, and acting reliably in real-world systems.This course is designed to help you understand how AI agents actually work under the hood, with a sharp focus on tool calling using LangChain.Rather than overwhelming you with large, flashy demos, the course builds a strong conceptual foundation so you can design agent systems that are correct, predictable, and scalable.What This Course Teaches YouThis course focuses on one critical question:How does an AI agent decide when and how to use a tool?You will learn:• How agents reason before taking action• Why tool calling is different from simple function calls• When to use built-in tools versus custom tools• How LangChain structures tool
descriptions and execution• How agents select the right tool based on user intent• Common mistakes that cause agent systems to behave incorrectlyBy the end of the course, tools will no longer feel magical or confusing. They will feel like controlled, intentional building blocks inside an agent system.How This Course Is DifferentMany courses jump straight into building large agent systems without explaining why things work.This course takes the opposite approach.It helps you think like an agent designer, not just a coder. You will understand reasoning loops before writing complex logic, avoid fragile architectures caused by over-trusting tools, and build intuition that carries forward into more advanced agent systems.The emphasis is on clarity, correctness, and design thinking, not hype.Hands-On, Without OverwhelmYou will see guided walkthroughs of built-in tools such as the calculator, how tools are registered and exposed to agents, and how an agent reasons before choosing a tool.An optional advanced code walkthrough is included for learners who want to explore deeper implementations.Advanced code is intentionally separated so beginners are not blocked, while experienced learners still gain value.
Who This Course Is ForThis course is ideal for:• Developers new to AI agents• Engineers exploring LangChain• Product managers and architects working with AI systems• Anyone who wants to understand how agent decisions actually workNo prior agent experience is required. Basic Python familiarity is helpful but not mandatory.What You Will Walk Away WithBy the end of this course, you will be able to:• Explain how an AI agent reasons and acts• Decide when a tool is truly needed• Design cleaner, safer agent workflows• Confidently talk about tool calling in interviews or project discussionsMost importantly, you will gain a mental model that scales beyond this course.Final ThoughtsTools do not make agents intelligent. Decisions do.This course helps you design those decisions correctly.
Who this course is forBeginners who want to understand AI agents without jumping into complex frameworks
Software developers curious about LangChain and agent tool calling fundamentals
Product managers, architects, and consultants working with AI systems
Anyone preparing for AI, GenAI, or agent-based interviews and projects
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