Program profile · official sources
Document AI: From OCR to Agentic Doc Extraction
DeepLearning.AI and LandingAI teach document processing from traditional OCR to agentic extraction. Learners work with layout detection, reading order and vision language models, then use LandingAI Agentic Document Extraction to produce structured Markdown and JSON. Examples integrate document extraction with RAG, AWS pipelines and a research-paper chatbot using Strands Agents. Basic Python familiarity is recommended.
Facts checked 15 Oct 2026
- Price
- See pricing
As shown in the United States on 15 October 2026, the page does not display a numeric fee. Embedded metadata categorizes an offer as Free, while visible copy associates accomplishments and graded features with Pro. The scope of that embedded free offer is not established; no free credential or numeric enrollment price is inferred.
- Provider link
See price and enroll at DeepLearning.AI (official site) ↗
Official site. No commission.
- Time
- 3h11m listed course duration; individual activity estimates are rounded
- Level
- Intermediate
- Credential
- Accomplishment with Pro
- Prerequisites
- Basic familiarity with Python is recommended.
- Format
- Online course with video lessons and listed learning activities
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Sources ↗
No accepted numeric price in this registry. See the sourced pricing details below.
See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.
What’s covered
- Introduction
- Document Processing Basics
- Lab 1: Document Processing with OCR
- Four Decades of OCR Evolution
- Lab 2: Document Processing with PaddleOCR
- Layout Detection and Reading Order
- Lab 3: Building Agentic Document Understanding
- A Single API for Agentic Document Understanding
- Lab 4: Document Understanding with Agentic Document Extraction
- Lab 4: Document Understanding with Agentic Document Extraction II
- Agentic Document Extraction for RAG
- Lab 5: Agentic Document Extraction for RAG
- Building RAG Pipelines with Agentic Document Extraction on AWS
- Lab 6: Building a Research Paper Chatbot with Strands Agents
- Conclusion
- Quiz
- Links & Resources
Prerequisites: Basic familiarity with Python is recommended.
What you actually do
- Introduction : 3m; Video; provider outline item, not a separately named module · Source
- Document Processing Basics : 8m; Video; provider outline item, not a separately named module · Source
- Lab 1: Document Processing with OCR : 13m; Video with Code Example; provider outline item, not a separately named module · Source
- Four Decades of OCR Evolution : 8m; Video; provider outline item, not a separately named module · Source
- Lab 2: Document Processing with PaddleOCR : 18m; Video with Code Example; provider outline item, not a separately named module · Source
- Layout Detection and Reading Order : 12m; Video; provider outline item, not a separately named module · Source
- Lab 3: Building Agentic Document Understanding : 14m; Video with Code Example; provider outline item, not a separately named module · Source
- A Single API for Agentic Document Understanding : 6m; Video; provider outline item, not a separately named module · Source
- Lab 4: Document Understanding with Agentic Document Extraction : 15m; Video with Code Example; provider outline item, not a separately named module · Source
- Lab 4: Document Understanding with Agentic Document Extraction II : 12m; Video with Code Example; provider outline item, not a separately named module · Source
- Agentic Document Extraction for RAG : 14m; Video; provider outline item, not a separately named module · Source
- Lab 5: Agentic Document Extraction for RAG : 9m; Video with Code Example; provider outline item, not a separately named module · Source
- Building RAG Pipelines with Agentic Document Extraction on AWS : 14m; Video; provider outline item, not a separately named module · Source
- Lab 6: Building a Research Paper Chatbot with Strands Agents : 16m; Video; provider outline item, not a separately named module · Source
- Conclusion : 1m; Video; provider outline item, not a separately named module · Source
- Quiz : 10m; Graded; provider outline item, not a separately named module · Source
- Links & Resources : 10m; Reading; provider outline item, not a separately named module · Source
What the credential is
- Credential type
- Accomplishment with Pro · www.deeplearning.ai / document-ai-from-ocr-to-agentic-doc-extraction
- Credential
- Accomplishment with Pro · www.deeplearning.ai / document-ai-from-ocr-to-agentic-doc-extraction
- Exam requirement
- A graded quiz is listed; its passing threshold and any separate final examination are not stated. · www.deeplearning.ai / document-ai-from-ocr-to-agentic-doc-extraction
- Credential scope
- As checked on 15 October 2026, the course page identifies an accomplishment with Pro, not an explicitly named academic or professional certification. The capture does not establish an independent credential issuer, full completion thresholds, expiry, renewal or academic-credit eligibility. · www.deeplearning.ai / document-ai-from-ocr-to-agentic-doc-extraction
Source differences retained
As checked on 15 October 2026, the official page gives differing information on the points below. Each reading is kept as found; none is reconciled.
- Duration: Visible course duration is 3h11m; same-course embedded metadata has generic courseWorkload PT1H. The visible duration is retained as text; no single numeric completion estimate is used. · Source
- Language: As checked on 15 October 2026, the same-course structured metadata states inLanguage="en" and availableLanguage=["en","jp","kr"]. English is retained; the additional literal codes do not establish whether they describe teaching audio, subtitles or another language option. No additional delivery language is verified. · Source
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Change log
- : Initial source review from the dated US capture. · Source
See price and enroll at DeepLearning.AI (official site) ↗
Official site. No commission.