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Kurs zawiera
- 16 godz. 36 min wideo
- 34 lekcji
- Poziom: Średnio zaawansowany
- Język: English
- Pamiętamy, gdzie skończyłeś
- W całości za darmo, bez karty
Lekcje
4 sekcji · 34 lekcje · 16 godz. 36 min łączna długość
Lekcje 1–1010 lekcji · 3 godz. 3 min
- India's Best GenAI Course Launch 2026 | Build 10+ Projects | Python + LangChain + AWS Bedrock17 min
- #1 What is GenAI? | ML vs DL vs GenAI Explained | Complete GEN-AI Series #genai #techsimplus8 min
- #2 How LLM Works? | LLM Explained: GPT Architecture | Build Tokeniser in Python #genai #llm22 min
- #3 GenAI Project Setup from Basic | OpenAI, Google Gemini, Claude, Groq & HuggingFace APIs #genai13 min
- #4 LangChain Explained | Build Your First QnA Chatbot using LangChain & OpenAI28 min
- #5 Multiple LLM Models with LangChain | OpenAI, Google Gemini & Anthropic #genai #langchain #gemini17 min
- #6 Prompt Engineering & LLM's with LangChain | Prompt Chains with LangChain #genai #llm24 min
- #7 End To End LLM QnA Chatbot with LangChain, Google Gemini and Streamlit | Gen-AI Project #llm23 min
- #8 Add Memory to AI Chatbot | LangChain Message History Tutorial #genai #llm #langchain14 min
- #9 Structured Output In LangChain | Generative AI using LangChain and Python #genai #langchain #llm17 min
Lekcje 11–2010 lekcji · 2 godz. 45 min
- #10 Learn Ollama in 10 Minutes - Run LLM Models Locally for FREE | Connect Ollama with LangChain9 min
- #11 Open Source LLM Models using Groq | Groq Integration with LangChain | 20x Faster than ChatGPT!10 min
- #12 Stream LLM Responses in Real-Time Like ChatGPT | Complete GenAI Tutorial with LangChain Python8 min
- #13 AI Agents Explained | What are AI Agents? | Build AI Agents with Python & LangChain #aiagents11 min
- #14 Building AI Agents from Scratch using LangChain, OpenAI & Python | Build Your First AI Agent17 min
- #15 Build Google Search AI Agent with Python & LangChain | OpenAI, Google Gemini #aiagents #google16 min
- #16 Build AI Agent with Memory & Conversation History | Google Search AI Agent with Memory #aiagents10 min
- #17 QnA Chatbot Faster Than ChatGPT | Streamlit + Groq + LangChain #genai #groq #langchain27 min
- #18 Build Sql AI Agent using LangChain, Groq & OpenAI | AI Task Manager using Groq #aiagents #groq40 min
- #19 What is RAG ? | RAG Pipeline Explained | RAG Vs LLMs #rag #genai #llm16 min
Lekcje 21–3010 lekcji · 4 godz. 21 min
- #20 Data Loading in RAG Pipeline | Build RAG Application using LangChain #rag #langchain24 min
- #21 Text Splitting for RAG Systems | RecursiveCharacterTextSplitter in LangChain #rag #genai13 min
- #22 Vector Embeddings & Vector Databases Explained | OpenAI Embeddings + ChromaDB + LangChain #genai23 min
- #23 Build Complete RAG-Based PDF QnA Chatbot | Building Production-Ready RAG Chatbot #genai #ai27 min
- #24 Build Agentic RAG System from Scratch | Agentic RAG Pipeline | Advanced RAG with AI Agents #ai24 min
- #25 End-to-End RAG Chatbot with PDF Upload | Streamlit + LangChain + Agentic RAG #rag #aiagents40 min
- #26 Pydantic Data Validation in Python | Pydantic Crash Course | PyDantic For GEN-AI Developers31 min
- #27 LangGraph Tutorial | Introduction to LangGraph with Python | Multi-Agent AI Systems Explained27 min
- #28 Build QnA Chatbot with Memory using LangGraph & GPT LLM | LangGraph QnA Chatbot #langgraph17 min
- #29 Build Multi AI Agentic System from Scratch using LangGraph | AI Agents with LangGraph #langgraph35 min
Lekcje 31–344 lekcje · 6 godz. 27 min
- #30 How to Build RAG Pipeline using LangGraph | Build RAG Based QnA System with Multiple Nodes21 min
- #31 LangGraph Human-in-the-Loop Explained | Add Human Approval to Your AI Agents (2026)41 min
- #32 Build a Multi-Agent Blog Generator with Human-in-the-Loop | LangGraph + LangChain #langgraph1 godz. 56 min
- AWS Bedrock Complete Course | Lambda, API Gateway, S3, RAG, Bedrock AgentCore & LangChain3 godz. 31 min
Czego potrzebujesz
- Podstawy się przydadzą: kurs zaczyna za nimi.
Opis
Master Generative AI from basics to advanced with Python, LangChain, LangGraph, AWS Bedrock, MCP Servers, and more. Build 10+ amazing AI projects with step-by-step tutorials in Hindi/Hinglish.
Dla kogo jest ten kurs
- Dla znających podstawy Python.
Te dwa punkty to nasz wniosek z poziomu kursu. Opis należy do autora.