Udemy - Complete RAG Bootcamp - Build, Optimize, and Deploy AI Ap...

Complete RAG Bootcamp: Build, Optimize, and Deploy AI Apps

https://WebToolTip.com

Published 10/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 6h 31m | Size: 3.97 GB

Learn to build intelligent, retrieval-powered AI systems using LangChain, LlamaIndex, and real-world RAG workflows

What you'll learn
Design and Build a Retrieval-Augmented Generation (RAG) System Understand how to integrate large language models (LLMs) with retrieval pipelines
Implement Embeddings and Vector Databases for Semantic Search Learn how to generate and store embeddings using tools like OpenAI, ChromaDB, or Pinecone
Develop an End-to-End AI Knowledge Assistant Build and deploy a functional AI chatbot using frameworks like LangChain, Streamlit, and FastAPI
Evaluate and Optimize AI Performance Metrics Measure your assistant’s accuracy, relevance, and user experience using key performance metrics

Requirements
Basic Python Programming Skills Familiarity with Python syntax and libraries (like pandas, requests, or json) will make it easier to follow along with code nstrations.
Curiosity About AI and LLMs A foundational understanding of how Large Language Models (LLMs) like ChatGPT or Llama work conceptually will be helpful, but not mandatory — everything is explained in simple terms.
Access to a Computer with Internet You’ll need a computer capable of running Python and Jupyter notebooks or VS Code, plus an internet connection to install packages and access APIs.
Free or Trial Accounts for Tools Some hands-on labs will use free-tier APIs or tools such as OpenAI, LangChain, ChromaDB, and Streamlit — setup instructions are provided in the course.