Document AI Masterclass
Build End-to-End Intelligent Document Pipelines
Updated on Jun, 2025
Language - English
Teaching and Academics ,Engineering,Computer Science
Lectures -5
Duration -3 hours
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Course Description
Master building an end-to-end, modular Document AI pipeline that extracts structured data from raw documents with OCR, layout analysis, and deep learning. The hands-on course guides you through real-world use cases—processing academic journals, forms, and reports—using tools like Tesseract, LayoutLM, and PyTorch to automate scale data extraction. Learn how to build a complete, modular Document AI pipeline to extract structured data from unprocessed documents using OCR, layout analysis, and deep learning. Interactive training allows the course to walk you through real-time examples—processing research papers, forms, and reports—using libraries like Tesseract, Lay out LM, and Torch to extract data at scale.
Goals
- Understand what Document AI is and its industry applications
- Build an end-to-end document processing pipeline
- Detect and interpret document layout and structure
- Extract and analyze visual and textual elements
- Process tables, charts, figures, and math expressions
- Integrate modules into a scalable, production-ready system
- Apply best practices for evaluation and deployment
- Understand what Document AI is and its industry applications
- Build an end-to-end document processing pipeline
- Detect and interpret document layout and structure
- Extract and analyze visual and textual elements
- Process charts, tables, figures, and mathematical expressions
- Combine modules into a scalable, production-ready system
- Use best-practice evaluation and deployment
Prerequisites
- Basic Python programming knowledge
- Familiarity with machine learning concepts (helpful, but not required)
- No prior experience with OCR or Document AI needed
Curriculum
Check out the detailed breakdown of what’s inside the course
Technical Section
2 Lectures
-
Overview
01:30:39
01:30:39
-
Course Code
02:01
02:01
Practical Section
2 Lectures
Conclusion Remarks
1 Lectures
Instructor Details
MADALI Nabil, Ph.D
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