Generative AI Beginner to Advance Tutorials in 2025 | Langchain Components - Model| Gen AI Tutorials

Learn Generative AI App development from basic to advance level using Lang-chain, Lang-graph, Lang-Smith, Vector DB, Pinecone, Fine-Tuning,
OpenAI, Hugging Face, Google gemini, Perplexity etc.

Complete Generative AI Tutorials from basic to advance in 2025

🚀 Welcome to Chapter 7 of our Generative AI basic to advance series in 2025 ! In this video, we dive deep into LangChain Model Components — the core building blocks that power every GenAI application.

👉 What you’ll learn:
1.Difference between LLM, ChatModel, and Embedding Models in LangChain
2.How to use closed-source LLMs (OpenAI GPT, Anthropic Claude) via APIs
3.How to integrate open-source models from Hugging Face (endpoints & locally hosted)

Best practices for choosing the right model for RAG, chatbots, and AI agents

Practical demo of connecting models with LangChain

🔹 Whether you’re a beginner or building advanced GenAI apps, this tutorial gives you a complete understanding of how models plug into LangChain.

💡 Perfect for:
AI enthusiasts, Data Scientists, ML Engineers, and anyone exploring Generative AI, LLMOps, or LangChain development.

✨ Don’t miss the upcoming chapters where we cover LangGraph, RAG pipelines, and Agentic AI frameworks!

📌 Keywords: LangChain tutorial, LangChain LLM, ChatModel, Embeddings, Hugging Face, OpenAI, Anthropic, Claude, Llama 2, Generative AI 2025, RAG, Local LLMs, AI Agents, MLOps, LangChain beginners, build AI chatbot.

Generative Tutorial for Data science enthusiast. Latest Gen AI complete tutorial

Components of Lang-chain
A. Model
B. Prompt
C. Chains
D. Memory
E. Indexes - RAG
F. Agents

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#genai #langchain #langgraph #googlegeminiai #openai #agent #machinelearning #deeplearning #aieducation #ai #datascience #dataanalytics #nlp #education #tutorial #ml #artificialintelligence

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