Build AI Agents with LangChain Tool Calling Essentials

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Free Download Build AI Agents with LangChain Tool Calling Essentials
Published 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

Tool calling, agent reasoning, and decision-driven AI design
What you'll learn
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
Requirements
Basic 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
Description
Build 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 for
Beginners 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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1.24 GB | 1min 17s | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English​

Files Included :

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FileName :1 Welcome to the Course.mp4 | Size: (4.03 MB)
FileName :2 How This Course Is Designed.mp4 | Size: (11.01 MB)
FileName :3 The Learning Journey Ahead.mp4 | Size: (4.45 MB)
FileName :4 Laying the Foundations for AI Agents.mp4 | Size: (4.6 MB)
FileName :5 Understanding the Building Blocks of AI Agents.mp4 | Size: (6.13 MB)
FileName :6 Designing How Agents Use Tools.mp4 | Size: (5.88 MB)
FileName :7 Applying Practicing and Consolidating Concepts.mp4 | Size: (10.12 MB)
FileName :8 Review and Assessment.mp4 | Size: (5.34 MB)
FileName :9 What You Will Gain from This Module.mp4 | Size: (4.32 MB)
FileName :10 How to Use This Course Effectively.mp4 | Size: (5.42 MB)
FileName :11 What exactly AI Agents are.mp4 | Size: (2.36 MB)
FileName :12 Shift in AI Systems.mp4 | Size: (5.98 MB)
FileName :13 Why Models alone are not enough.mp4 | Size: (2.97 MB)
FileName :14 Definition of AI Agents.mp4 | Size: (6.06 MB)
FileName :15 Core capabilities of AI Agents.mp4 | Size: (5.87 MB)
FileName :16 Example 1 Order groceries.mp4 | Size: (5.99 MB)
FileName :17 Example 2 Travel plan.mp4 | Size: (5.08 MB)
FileName :18 Agent loop.mp4 | Size: (4.7 MB)
FileName :19 Wnen are Agents powerful.mp4 | Size: (4.08 MB)
FileName :20 Wrap up.mp4 | Size: (1.64 MB)
FileName :21 Why we need AI Systems.mp4 | Size: (47.95 MB)
FileName :22 Monolithic Vs Compund AI systems.mp4 | Size: (13.65 MB)
FileName :23 Limitations of LLMs only approach.mp4 | Size: (10.3 MB)
FileName :24 How agents help.mp4 | Size: (9.9 MB)
FileName :25 Key Insights You Should Remember.mp4 | Size: (3.99 MB)
FileName :26 AI Agent Architecture Introduction.mp4 | Size: (10.66 MB)
FileName :27 What Does Architecture Mean in Agentic AI.mp4 | Size: (17.29 MB)
FileName :28 High Level Agent Architecture.mp4 | Size: (16.27 MB)
FileName :29 Component Policy.mp4 | Size: (18.9 MB)
FileName :30 Component Memory.mp4 | Size: (17.75 MB)
FileName :31 Component Tools.mp4 | Size: (46.86 MB)
FileName :32 Tool Invocation Flow.mp4 | Size: (14.34 MB)
FileName :33 Component Reasoning Loop.mp4 | Size: (16.19 MB)
FileName :34 Component Environment.mp4 | Size: (11.5 MB)
FileName :35 Agent Blueprint Overview.mp4 | Size: (13.75 MB)
FileName :36 Mini Code Demo Simple Agent.mp4 | Size: (15.98 MB)
FileName :37 Runtime Flow of an Agent.mp4 | Size: (20 MB)
FileName :38 Real World Example Travel Planner Agent.mp4 | Size: (17.81 MB)
FileName :39 Recap.mp4 | Size: (9.8 MB)
FileName :40 One last word.mp4 | Size: (3.24 MB)
FileName :41 Types of Tools for AI Agents Introduction.mp4 | Size: (15.21 MB)
FileName :42 What Are Tools in AI Agents.mp4 | Size: (13.44 MB)
FileName :43 Information Retrieval Tools.mp4 | Size: (13.57 MB)
FileName :44 Calculation & Logic Tools.mp4 | Size: (21.48 MB)
FileName :45 API & Service Tools.mp4 | Size: (12.38 MB)
FileName :46 Data Processing Tools.mp4 | Size: (13.46 MB)
FileName :47 Knowledge Tools.mp4 | Size: (13.1 MB)
FileName :48 Action Tools.mp4 | Size: (13.41 MB)
FileName :49 Composite Tools.mp4 | Size: (13.82 MB)
FileName :50 How To Choose The Right Tool.mp4 | Size: (19.25 MB)
FileName :51 Tool Selection Scenarios.mp4 | Size: (12.02 MB)
FileName :52 Mini Code Demo Search + Math Tool Example.mp4 | Size: (13.27 MB)
FileName :53 Recap.mp4 | Size: (13.8 MB)
FileName :54 Before we close.mp4 | Size: (6.15 MB)
FileName :56 From Capability to Control in AI Tool Calling.mp4 | Size: (19.84 MB)
FileName :57 Traditional Tool Calling Explained.mp4 | Size: (23.58 MB)
FileName :58 Embedded Tool Calling and Controlled Execution.mp4 | Size: (20.54 MB)
FileName :59 Choosing Between Traditional and Embedded Tool Calling.mp4 | Size: (22.47 MB)
FileName :60 Tool Calling in Practice Traditional vs Structured.mp4 | Size: (30.28 MB)
FileName :61 Key Takeaways and What Comes Next.mp4 | Size: (9.33 MB)
FileName :63 Setting the Foundation.mp4 | Size: (9.98 MB)
FileName :64 How Agents Choose Tools.mp4 | Size: (13.2 MB)
FileName :65 Design Patterns & Pitfalls.mp4 | Size: (13.87 MB)
FileName :66 Architecture Outcomes.mp4 | Size: (22.09 MB)
FileName :67 What This Enables You to Build.mp4 | Size: (3.71 MB)
FileName :69 Designing Effective Tools for AI Agents.mp4 | Size: (10.73 MB)
FileName :70 Designing Tools Is a Design Problem.mp4 | Size: (13.16 MB)
FileName :71 What Makes a Tool Effective.mp4 | Size: (6.55 MB)
FileName :72 Human Friendly vs Agent Friendly Tools.mp4 | Size: (6.02 MB)
FileName :73 Single Responsibility Principle.mp4 | Size: (14.02 MB)
FileName :74 Why Smaller Tools Work Better.mp4 | Size: (3.19 MB)
FileName :75 Writing Agent Friendly Descriptions.mp4 | Size: (7 MB)
FileName :76 Good vs Bad Tool Descriptions.mp4 | Size: (3.91 MB)
FileName :77 Designing Clear Inputs.mp4 | Size: (7.13 MB)
FileName :78 Designing Reliable Outputs.mp4 | Size: (8.78 MB)
FileName :79 Mini Code Demo Designing a Well Behaved Tool.mp4 | Size: (14.91 MB)
FileName :80 Why Structure Matters.mp4 | Size: (4.99 MB)
FileName :81 Structured Tools as Guardrails.mp4 | Size: (4.17 MB)
FileName :82 Mini Code Demo.mp4 | Size: (8.19 MB)
FileName :83 Designing Tools for Agent Decision Confidence.mp4 | Size: (11.29 MB)
FileName :84 Key Takeaways.mp4 | Size: (12.65 MB)
FileName :85 Thank You.mp4 | Size: (2.41 MB)
FileName :87 Intelligent Agents Are Not All the Same.mp4 | Size: (6.28 MB)
FileName :88 From Static to Reasoned Systems.mp4 | Size: (12.11 MB)
FileName :89 Zero Shot Agents.mp4 | Size: (11.89 MB)
FileName :90 ReAct Agents.mp4 | Size: (4.7 MB)
FileName :91 Why ReAct Is More Reliable.mp4 | Size: (5.29 MB)
FileName :91 Why ReAct Is More Reliable Resource 1 9 5 mp4.mp4 | Size: (2.42 MB)
FileName :92 Multi Tool Agents.mp4 | Size: (13.76 MB)
FileName :93 How Agents Choose Tools.mp4 | Size: (10.3 MB)
FileName :94 Intelligence Through Orchestration.mp4 | Size: (9.79 MB)
FileName :95 Choosing the Right Agent Pattern.mp4 | Size: (6.21 MB)
FileName :96 Common Misconceptions.mp4 | Size: (7.43 MB)
FileName :97 Key Takeaways.mp4 | Size: (8.42 MB)
FileName :98 Thank You and what comes next.mp4 | Size: (8.25 MB)
FileName :100 Lesson Objective Building a Custom Math Toolkit Agent.mp4 | Size: (4.27 MB)
FileName :101 From Agent Patterns to Tool Based Design.mp4 | Size: (14.87 MB)
FileName :102 From Agent Patterns to Tool Based Design.mp4 | Size: (15.82 MB)
FileName :103 Registering a Custom Tool with LangChain.mp4 | Size: (10.76 MB)
FileName :104 Running the Custom Math Toolkit Agent.mp4 | Size: (5.61 MB)
FileName :105 Interpreting the Agent's Response.mp4 | Size: (4.46 MB)
FileName :106 Understanding Agent Behavior After Tool Execution.mp4 | Size: (5.1 MB)
FileName :107 Key Takeaways from Building a Custom Tool Agent.mp4 | Size: (2.49 MB)
FileName :109 Introduction to LangChain Built in Tools.mp4 | Size: (19 MB)
FileName :110 Choosing Between Built in and Custom Tools.mp4 | Size: (10.22 MB)
FileName :111 Built in Tool Categories and Quick Demos (Search & Browser).mp4 | Size: (17.73 MB)
FileName :112 Calculator Tool Demo and Agent Tool Selection Logic.mp4 | Size: (44.32 MB)
FileName :113 Course Wrap Up Takeaways what next.mp4 | Size: (11.8 MB)
FileName :115 Course Summary.mp4 | Size: (21.47 MB)

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