Complete Agentic AI Course In 10 Hours- Langchain, Langgraph, RAG,Vectorless RAG, Guardrails,Evals

Why It Matters

By consolidating the latest LangChain updates, RAG innovations, and safety mechanisms into a single, actionable guide, the video accelerates skill acquisition and helps organizations deploy trustworthy, high‑performance agentic AI solutions faster.

Key Takeaways

• 10.5‑hour tutorial covers latest LangChain v1 updates for developers
• Includes LangGraph crash course and agentic RAG implementations
• Demonstrates vectorless RAG vs traditional vector‑based retrieval techniques
• Shows setup using UV package manager and virtual environments
• Covers guardrails, evaluation methods, and LLM gateway integration

Summary

Krush Nayak’s 10.5‑hour video serves as a masterclass on the newest generative and agentic AI tools, focusing on LangChain v1, LangGraph, Retrieval‑Augmented Generation (RAG) variants, security guardrails, and LLM evaluation. The tutorial walks viewers through the updated LangChain ecosystem—new middleware, short‑term memory, diverse message types, and agent creation—while also delivering a crash course on LangGraph for building sophisticated agentic applications.

Key sections include a deep dive into traditional RAG, the emerging concept of agentic RAG, and a side‑by‑side comparison of vector‑based versus vectorless RAG approaches. Nayak also introduces “deep agents” for advanced research tasks, demonstrates how to implement guardrails for AI safety, and explores open‑source evaluation frameworks and LLM gateway integrations.

Throughout the session, Nayak emphasizes practical setup using the UV package manager, showcasing rapid virtual‑environment creation, dependency handling, and installation of the latest LangChain libraries. He highlights tools like Google Antigravity IDE and provides concrete code snippets, reinforcing his claim that mastering this material equips viewers for technical interviews and real‑world deployments.

The video’s breadth makes it a one‑stop resource for developers and enterprises aiming to adopt cutting‑edge agentic AI, streamline development pipelines, and embed robust security and evaluation practices into their LLM workflows.

Original Description

This is a complete course on learning Generative ai and agentic with Langchain and Langgraph. We have included all the topics from RAG, vectorless rag, Deep agents, Guardrails, LLM Evaluation and LLM Gateways Techniques

Github Links

Langchain : https://github.com/krishnaik06/Langchain-V1-Crash-Course

Langgraph: https://github.com/krishnaik06/Agentic-LanggraphCrash-course

RAG: https://github.com/krishnaik06/RAG-Tutorials

Vectorless RAG: https://github.com/krishnaik06/RAG-Tutorials/blob/main/PageIndex_Vectorless_RAG_CrashCourse%20(1).ipynb

Deep Agents: https://drive.google.com/file/d/1SVjvgqvKfF-FPAIqpEZdKMQLhe13NLFD/view

Guardrails : https://github.com/krishnaik06/Langchain-V1-Crash-Course/blob/main/updatedlangchain/langchain_guardrails_crash_course.ipynb

LLM Evals : https://github.com/krishnaik06/RAG-Tutorials/blob/main/1-rag_evaluation.ipynb

LLM Gateways: https://github.com/krishnaik06/Langchain-V1-Crash-Course/blob/main/llm_gateway_tutorial.ipynb

Timestamp

00:00:00 Introduction

00:02:31 Langchain Course

02:35:12 Langraph Course

05:02:29 RAG Course

07:10:43 Vectorless RAG

08:02:11 Deep Agents

08:45:43 Guardrails

09:22:55 LLM Evaluation

10:30:25 LLM Gateways

-------------------------------------------------------------------

Learn from us visit https://krishnaik.in/liveclasses