Description
AI Engineering: The Complete RAG Course is a course on designing, building, evaluating, and deploying retrieval-augmented applications (RAG) with modern AI engineering techniques published by Udemy Online Academy. Designed for AI engineers, Python developers, software engineers, machine learning specialists, and developers working with large language models, the course covers the complete RAG workflow from document ingest and preprocessing to retrieval, production, evaluation, and production deployment. Students will learn about embeddings, vector databases, semantic and combinatorial search, segmentation strategies, retrieval optimization, re-ranking, metadata filtering, rapid engineering, LLM integration, RAG evaluation, agent-based RAG, and scalable deployment patterns.
In this course, you will build a fully production-ready RAG application from scratch using Python, FastAPI, ChromaDB, Gradio, and modern large language models including OpenAI, Gemini, Groq, and open source models. In this course, you will learn how RAG works from the ground up and build a complete RAG application step by step using Python, FastAPI, ChromaDB, Gradio, and modern large language models (LLM). By the end of this course, you will understand how modern RAG systems work internally and have built a complete, production-ready RAG application with a FastAPI backend and a Gradio web interface that you can extend with your own documentation, models, and features.
What you will learn in AI Engineering: The Complete RAG Course :
- Build complete Retrieval-Augmented Generation (RAG) applications using Python, FastAPI, and modern AI tools.
- Integrate OpenAI, Google Gemini, Groq, and open-source models into real-world RAG systems.
- Ingest, chunk, embed, and retrieve data from documents to create accurate AI-powered applications.
- Build production-ready APIs with FastAPI and deploy RAG applications with best practices.
- and …
Course specifications
Publisher: Udemy
Instructors: Ahmed Sawy
Language: English
Level: Introductory to Advanced
Number of Lessons: 55
Duration: 3h 17m
Course topics on 2026/8
AI Engineering: The Complete RAG Course Prerequisites
Basic Python knowledge is recommended (variables, functions, loops, and classes).
No prior AI, Machine Learning, or RAG experience is required.
Pictures
AI Engineering: The Complete RAG Course introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
2.4 GB