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A complete crash course on agentic ai using langchain. This is also a course on generative AI. In this video, we will discuss theoratical foundations of generative AI and agentic AI. Langchain will be used for hands on programming. We will then build two projects (1) shopping agent (2) telecom RAG chatbot using langchain, chromadb, llama vision model, Qwen, gemini LLMs, streamlit, sqlite, huggingface and sentence transformers.

Download the resources here: https://codebasics.io/resources/agentic-ai-crash-course

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Langgraph tutorial: https://youtu.be/CnXdddeZ4tQ
Customer care support: https://youtu.be/Jekzc6BM5_w
Workflow automation: https://youtu.be/QBI5bmbgL38

Check out OpenRouter: https://openrouter.plug.dev/6QpCcgh

Codebasics AI Pro keeps you ahead of it: weekly tool tests, live build sessions, and AI you can actually apply at work: https://codebasics.io/ai-learning-for-professionals

⭐️ Timestamps ⭐️

0:00:00 Intro

0:01:53 What is Gen AI

0:03:10 Traditional AI

0:05:41 Transformer Architecture

0:11:13 LLM Parameters

0:13:28 LLM Analogy Based Explanation

0:18:41 API Key Setup

0:21:01 Simple LLM call using LangChain

0:41:50 RAG Theory

0:47:52 Vector DB – Hands On

0:53:50 Rag – Hands On

1:02:54 AI Agent Intro

1:03:31 What is an AI Agent

1:10:18 ReAct Loop

1:10:49 AI Agent Hands on

1:21:28 Multi-Agent system

1:21:48 Multi-Model Agent theory

1:23:31 Multi-modal agent – hands on

1:29:28 Evaluation

1:34:07 Guardrails

1:36:41 Project 1 – Shopping Agent

2:06:57 Project 2 – Telecom RAG

2:22:46 No Code Agents

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