Intelligent Document Processing (IDP) with OCR Tools

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About Course

Unlock the power of automation with our comprehensive Intelligent Document Processing (IDP) with OCR Tools online training. This course is designed to equip professionals, developers, and automation enthusiasts with the skills needed to digitize, extract, and process data from various types of documents using AI-driven OCR (Optical Character Recognition) tools.

Through hands-on lessons and real-world projects, you’ll learn how to implement IDP solutions that handle structured, semi-structured, and unstructured documents — such as invoices, forms, receipts, and ID cards — with high accuracy and minimal manual effort.

What Will You Learn?

  • Understand the fundamentals of Intelligent Document Processing (IDP) and its integration with RPA and AI
  • Use OCR technologies such as Tesseract, UiPath, ABBYY, and Google Vision to extract data from PDFs, images, and scanned documents
  • Apply document pre-processing techniques using Python and OpenCV to enhance OCR accuracy
  • Classify and process structured, semi-structured, and unstructured documents
  • Perform data extraction using regular expressions, table recognition, and NLP-based methods
  • Automate document workflows using UiPath Document Understanding and other platforms
  • Integrate OCR output with databases, spreadsheets, and APIs
  • Handle validation processes, exceptions, and confidence levels effectively
  • Build and deploy real-world IDP projects, including invoice automation, ID card recognition, and form extraction
  • Follow best practices for creating secure, scalable, and enterprise-ready document automation solutions

Course Content

Module 1: Introduction to Intelligent Document Processing
What is IDP? Evolution of document processing Use cases in finance, healthcare, logistics, legal, etc. IDP vs OCR vs RPA – Differences and synergy Key components: OCR, NLP, AI, ML, Workflow Automation

Module 2: Understanding OCR (Optical Character Recognition)
Introduction to OCR How OCR works: image to text Types of OCR: Printed vs Handwritten Challenges in OCR (noise, skew, low resolution, etc.) OCR accuracy metrics

Module 3: OCR Tools Overview
Tesseract OCR – Setup and usage ABBYY FlexiCapture – Features and applications UiPath Document Understanding – Architecture and setup Google Cloud Vision / Azure Form Recognizer overview Comparison of OCR engines

Module 4: Document Types & Preprocessing Techniques
Structured, semi-structured, and unstructured documents Scanned images, PDFs, handwritten forms Image pre-processing using Python and OpenCV Noise reduction, binarization, skew correction, cropping Improving OCR accuracy with preprocessing

Module 5: Data Extraction Techniques
Zonal vs Intelligent data extraction Regular expressions and pattern matching Table extraction techniques Named Entity Recognition (NER) for unstructured documents Working with multi-page documents

Module 6: Hands-On Projects
Invoice data extraction (Tesseract + Python) ID card or passport data recognition Form processing with UiPath Document Understanding Receipt data processing with Google Vision OCR Resume parser using NLP + OCR

Module 7: Integration with RPA and APIs
Connecting OCR with RPA tools (UiPath, Automation Anywhere) Working with OCR APIs (Google, Azure, AWS Textract) Building end-to-end workflows Storing extracted data in databases, Excel, and cloud systems

Module 8: Validation, Exceptions, and Post-Processing
Human-in-the-loop validation Error handling and accuracy improvement Post-processing: Formatting, cleansing, and structuring data Confidence scores and thresholds

Module 9: IDP in Enterprise Applications
Compliance, security, and data privacy Scalability and performance considerations Real-world case studies ROI and cost-benefit analysis

Module 10: Final Project & Certification
Capstone Project: End-to-end IDP workflow Project presentation (optional for live courses) Course summary and final assessment Certification of Completion

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