Program profile · official sources

Orchestrating Workflows for GenAI Applications

DeepLearning.AI and Astronomer teach orchestration with Apache Airflow 3.0. Learners turn a notebook-based book-recommendation RAG prototype into separate ingestion and query pipelines, apply time-based and data-aware scheduling, and use dynamic task mapping. Retries, failure alerts and backfills support reliable operation. Python familiarity is expected, while Airflow experience is unnecessary. The outline retains an optional local-environment setup lesson, resources and a graded quiz.

Facts checked 15 Oct 2026

Price
Free
(As shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.)
Provider link

See price and enroll at DeepLearning.AI (official site) ↗

Official site. No commission.

Time
1h48m listed course duration
Level
Intermediate
Credential
DeepLearning.AI Accomplishment

The provider recommends sharing an Accomplishment screenshot, including on LinkedIn.

Prerequisites
Python familiarity is expected; no prior Airflow experience is required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Format
Online self-paced learning with video lessons and listed activities

Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.

This program is free. It is not plotted on the logarithmic price scale. 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
  • From Notebook To Pipeline
  • Your RAG Prototype
  • Building a Simple Pipeline
  • Turning your Prototype into a Pipeline
  • Scheduling and Dag Parameters
  • Make the Pipeline Adaptable
  • Prepare to Fail
  • GenAI pipelines in Real Life
  • Conclusion
  • Quiz
  • Optional: How to Set up a Local Airflow Environment
  • Appendix - Resources, Help, and Downloads

Prerequisites: Python familiarity is expected; no prior Airflow experience is required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.

Explore DeepLearning.AI

What you actually do

  • Introduction : 3m; Video; provider outline item · Source
  • From Notebook To Pipeline : 9m; Video; provider outline item · Source
  • Your RAG Prototype : 8m; Video with Code Example; provider outline item · Source
  • Building a Simple Pipeline : 11m; Video with Code Example; provider outline item · Source
  • Turning your Prototype into a Pipeline : 9m; Video with Code Example; provider outline item · Source
  • Scheduling and Dag Parameters : 10m; Video with Code Example; provider outline item · Source
  • Make the Pipeline Adaptable : 11m; Video with Code Example; provider outline item · Source
  • Prepare to Fail : 11m; Video with Code Example; provider outline item · Source
  • GenAI pipelines in Real Life : 6m; Video; provider outline item · Source
  • Conclusion : 1m; Video; provider outline item · Source
  • Quiz : 10m; Graded; provider outline item · Source
  • Optional: How to Set up a Local Airflow Environment : 3m; Video; provider outline item · Source
  • Appendix - Resources, Help, and Downloads : 10m; Code Example; provider outline item · Source

What the credential is

Credential type
DeepLearning.AI Accomplishment · www.deeplearning.ai / orchestrating-workflows-for-genai-applications
Credential
DeepLearning.AI Accomplishment · info.deeplearning.ai / draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
Issuer
DeepLearning.AI · info.deeplearning.ai / draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
Sharing
The provider recommends sharing an Accomplishment screenshot, including on LinkedIn. · info.deeplearning.ai / draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
Exam requirement
The outline lists 1 graded assignment. A separate comprehensive final examination and passing threshold are not stated. · www.deeplearning.ai / orchestrating-workflows-for-genai-applications
Credential scope
As checked on 15 October 2026, Pro subscribers completing this short course receive an Accomplishment visible in their account. It is explicitly not an official certificate. Free users do not receive certificates or accomplishments. Passing thresholds, separate final-exam requirements, expiry, renewal and academic credit are not established. The course header marks its 1 graded assignment as Pro access. Direct Pro membership upgrades take effect immediately. After a downgrade, access to content and eligibility to earn certificates continue until the next billing cycle, and progress on started courses is saved for 180 days. This does not turn short-course Accomplishments into official certificates. The seven-day trial can be cancelled to avoid charges. After the trial, new payments, renewals and upgrades are non-refundable; early cancellation or downgrade receives no partial refund, with access until the next renewal. Incorrect charges or charges after a trial cancellation may qualify for a full refund after support review. Eligible refunds typically take 5–10 business days, depending on the bank. These are direct-platform terms, not Coursera terms. · info.deeplearning.ai / draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses

Cost details

Membership and refund terms: As checked on 15 October 2026, direct Pro membership upgrades take effect immediately. After a downgrade, access to content and eligibility to earn certificates continue until the next billing cycle, and progress on started courses is saved for 180 days. This does not turn short-course Accomplishments into official certificates. The seven-day trial can be cancelled to avoid charges. After the trial, new payments, renewals and upgrades are non-refundable; early cancellation or downgrade receives no partial refund, with access until the next renewal. Incorrect charges or charges after a trial cancellation may qualify for a full refund after support review. Eligible refunds typically take 5–10 business days, depending on the bank. These are direct-platform terms, not Coursera terms. · Source · Source · Source · Source

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.

  • Language: As checked on 15 October 2026, the matching Course metadata states inLanguage="en" and availableLanguage=["en","jp","kr"]. English is retained; the additional literal codes do not establish teaching audio, subtitles or another language-option scope. · Source
  • Duration: The visible course duration is 1h48m; same-course embedded courseWorkload PT1H differs. No numeric completion estimate is inferred. · Source

Who should skip it

  • Free content access excludes certificates and Accomplishments; recognition requires Pro membership. The course header marks its 1 graded assignment as Pro access. · Official source · 2026-10-15
  • Short-course Accomplishments are not official certificates. · Official source · 2026-10-15

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Change log

  • : Initial source review from the dated US capture. · Source
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