Description
AI Document Intelligence: RAG, Agents & ML Data is a course on using modern AI techniques to understand, process, retrieve, and analyze documents, published by Udemy Online Academy. Students will learn how to transform unstructured data from PDFs, reports, contracts, invoices, and other documents into actionable insights through Retrieval Augmentation (RAG), AI agents, and machine learning workflows. Build a complete AI-powered document intelligence platform from scratch and learn how to transform unstructured PDFs into intelligent applications, structured datasets, AI agents, and machine learning-ready data.
This course covers document retrieval, text extraction, embeddings, vector databases, semantic search, agent-based automation, data enrichment, and LLM integration. Throughout the course, you will work on a realistic project and implement each core component yourself rather than relying on black-box frameworks. You’ll understand not only how the individual components work, but also how they fit together to create enterprise-level AI solutions. By the end of this course, you’ll have built a complete AI document intelligence platform capable of transforming raw PDFs into searchable knowledge, intelligent agent workflows, structured datasets, analytics-ready outputs, and machine learning-ready data pipelines.
What you will learn in AI Document Intelligence: RAG, Agents & ML Data:
- Build an end-to-end AI document intelligence platform using PDFs, RAG, AI Agents, FastAPI, React, and machine learning-ready datasets.
- Implement Retrieval-Augmented Generation (RAG) using ChromaDB, embeds, semantic search, and AI-powered responses.
- Design and develop AI agents that select tools, execute queries, and generate intelligent responses from documents and data.
- Transform unstructured PDF documents into structured, analytics-ready, and machine learning-ready datasets.
- Build FastAPI-style backend services to generate and expose AI, RAG, and Agent capabilities via REST APIs.
- Develop a modern React application to interact with RAG pipelines, AI agents, and document intelligence workflows.
- And…
Course specifications
Publisher: Udemy
Instructors: Rahul Sahay
Language: English
Level: Introductory to Advanced
Number of Lessons: 90
Duration: 11 hours and 50 minutes
Course topics on 2026/6
AI Document Intelligence: RAG, Agents & ML Data Prerequisites
Basic Python programming knowledge is recommended, but every concept is explained step-by-step.
No prior experience with RAG, AI Agents, ChromaDB, FastAPI, React, or Document Intelligence is required.
A computer capable of running Python applications and installing open-source packages.
Basic understanding of APIs, JSON, and software development concepts will be helpful.
A willingness to build real-world AI applications through hands-on project-based learning.
No prior Machine Learning or Data Science experience is required.
No prior experience with Vector Databases or LLM frameworks is needed.
Students should be comfortable using VS Code or any Python development environment.
Pictures
AI Document Intelligence: RAG, Agents & ML Data 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
10.6 GB
