Quick Guide & Tips

đŸ’»   Accessing Utils File and Helper Functions

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Open"

You will be able to see all the notebook files for the lesson, including any helper functions used in the notebook on the left sidebar. See the following image for the steps above.

🔄   Reset User Workspace

If you need to reset your workspace to its original state, follow these quick steps:

1:   Access the Menu: Look for the three-dot menu (⋼) in the top-right corner of the notebook toolbar.

2:   Restore Original Version: Click on "Restore Original Version" from the dropdown menu.

For more detailed instructions, please visit our Reset Workspace Guide.

đŸ’»   Downloading Notebooks

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Download as"

3:   Then, click on "Notebook (.ipynb)"

đŸ’»   Uploading Your Files

After following the steps shown in the previous section ("File" => "Open"), then click on "Upload" button to upload your files.

📗   See Your Progress

Once you enroll in this course—or any other short course on the DeepLearning.AI platform—and open it, you can click on 'My Learning' at the top right corner of the desktop view. There, you will be able to see all the short courses you have enrolled in and your progress in each one.

Additionally, your progress in each short course is displayed at the bottom-left corner of the learning page for each course (desktop view).

đŸ“±   Features to Use

🎞   Adjust Video Speed: Click on the gear icon (⚙) on the video and then from the Speed option, choose your desired video speed.

🗣   Captions (English and Spanish): Click on the gear icon (⚙) on the video and then from the Captions option, choose to see the captions either in English or Spanish.

🔅   Video Quality: If you do not have access to high-speed internet, click on the gear icon (⚙) on the video and then from Quality, choose the quality that works the best for your Internet speed.

đŸ–„   Picture in Picture (PiP): This feature allows you to continue watching the video when you switch to another browser tab or window. Click on the small rectangle shape on the video to go to PiP mode.

√   Hide and Unhide Lesson Navigation Menu: If you do not have a large screen, you may click on the small hamburger icon beside the title of the course to hide the left-side navigation menu. You can then unhide it by clicking on the same icon again.

🧑   Efficient Learning Tips

The following tips can help you have an efficient learning experience with this short course and other courses.

🧑   Create a Dedicated Study Space: Establish a quiet, organized workspace free from distractions. A dedicated learning environment can significantly improve concentration and overall learning efficiency.

📅   Develop a Consistent Learning Schedule: Consistency is key to learning. Set out specific times in your day for study and make it a routine. Consistent study times help build a habit and improve information retention.

Tip: Set a recurring event and reminder in your calendar, with clear action items, to get regular notifications about your study plans and goals.

☕   Take Regular Breaks: Include short breaks in your study sessions. The Pomodoro Technique, which involves studying for 25 minutes followed by a 5-minute break, can be particularly effective.

💬   Engage with the Community: Participate in forums, discussions, and group activities. Engaging with peers can provide additional insights, create a sense of community, and make learning more enjoyable.

✍   Practice Active Learning: Don't just read or run notebooks or watch the material. Engage actively by taking notes, summarizing what you learn, teaching the concept to someone else, or applying the knowledge in your practical projects.

📚   Enroll in Other Short Courses

Keep learning by enrolling in other short courses. We add new short courses regularly. Visit DeepLearning.AI Short Courses page to see our latest courses and begin learning new topics. 👇

👉👉 🔗 DeepLearning.AI – All Short Courses [+]

🙂   Let Us Know What You Think

Your feedback helps us know what you liked and didn't like about the course. We read all your feedback and use them to improve this course and future courses. Please submit your feedback by clicking on "Course Feedback" option at the bottom of the lessons list menu (desktop view).

Also, you are more than welcome to join our community 👉👉 🔗 DeepLearning.AI Forum

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DeepLearning.AI
Short CourseIntermediate

Document AI: From OCR to Agentic Doc Extraction

Instructors: David Park, Andrea Kropp

LandingAI logo
  • Intermediate
  • 15 Video Lessons
  • 6 Code Examples
  • Instructors: David Park, Andrea Kropp
    • LandingAI
    LandingAI

What you'll learn

  • Build agentic document processing pipelines that convert PDFs into structured Markdown and JSON by extracting text, tables, charts, and forms without losing context from layout.

  • Explore LandingAI’s Agentic Document Extraction (ADE) framework to parse complex files reliably with visual grounding and extract fields accurately through user-defined schemas.

  • Learn to deploy serverless RAG applications on AWS with event-driven document processing powered by LandingAI’s ADE framework.

About this course

Join this new short course on Document AI, built with LandingAI and taught by David Park, Senior Director of Applied AI, and Andrea Kropp, Applied AI Engineer at LandingAI.

Much of the world’s data is locked in PDFs, JPEGs, and other documents. Traditional OCR extracts text but loses critical information—the layout of tables with merged cells, the relationship between charts and captions, the reading order of multi-column layouts. This course shows you how to build agentic workflows that process documents the way humans do: breaking them into parts, examining each piece carefully, and extracting information through multiple iterations.

You’ll start by exploring traditional OCR. After understanding its limitations, you’ll build agents equipped with additional tools for document processing like layout detection, reading order, and multimodal reasoning models. Next, you’ll learn to use the Agentic Document Extraction (ADE) framework from LandingAI to automate this workflow. ADE treats documents as visual objects. It uses custom models to parse complex elements and ground extracted fields to precise locations on the page. You’ll integrate ADE into RAG applications and deploy them as production-ready pipelines on AWS.

In detail, you’ll:

  • Explore traditional OCR methods to extract text from documents. Understand their limitations when handling tables, handwriting, or scanned images.
  • Learn how OCR evolved from early shape-based classifiers to modern deep learning systems. Apply models for layout detection to chunk documents into regions of interest with bounding boxes.
  • Use models for reading order to sort information into logical sequences. Employ vision language models to capture both text and images from documents.
  • Process challenging features like attestations, formulas, or barcodes with LandingAI’s Agentic Document Extraction (ADE). Parse documents as Markdown and extract key-value pairs as JSON without losing context in layout.
  • Build a RAG application that preprocesses documents with ADE, stores parsed chunks in a vector database, and retrieves text for queries along with cropped images from the respective source documents.
  • Implement an event-driven pipeline on AWS that automatically triggers ADE on uploads to S3, loads parsed documents into a Bedrock Knowledge Base, and interrogates them with Strands Agents.

Document AI is transforming how organizations unlock value from unstructured data. Whether you’re handling financial invoices, medical records, or academic papers, this course gives you the tools and techniques to build systems for intelligent document processing.

Who should join?

AI builders and developers who want to automate the extraction of information from documents. Basic familiarity with Python is recommended to make the most of this course.

Course Outline

15 Lessons・6 Code Examples

Instructors

David Park

David Park

Andrea Kropp

Andrea Kropp

Additional learning features, such as quizzes and projects, are included with DeepLearning.AI Pro. Explore it today

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