Transform your data engineering capabilities with production-ready Apache Airflow workflows that eliminate manual intervention and ensure bulletproof reliability. This course empowers data engineers to move beyond simple task scheduling to architecting resilient, maintainable, and configurable automated pipelines that handle real-world complexities.
Automate Data Workflows with Airflow Excellence
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Automate Data Workflows with Airflow Excellence
This course is part of DataOps: Automation & Reliability Specialization
Instructor: Hurix Digital
Included with
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
1 hour to complete
Flexible schedule
Learn at your own pace
What you'll learn
Production-grade workflows require proactive failure handling strategies, not reactive troubleshooting approaches.
Parameterization and configuration management are essential for workflow reusability across different environments and datasets.
Task dependency design and SLA monitoring form the foundation of reliable data pipeline operations.
Robust workflow architecture prevents downstream business disruptions and reduces operational overhead.
Skills you'll gain
Details to know
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Recently updated!
January 2026
Assessments
3 assignments
Taught in English
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This course is part of the DataOps: Automation & Reliability Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 2 modules in this course
Learners will understand the foundational concepts and design principles for creating robust data workflows with Apache Airflow.Module Learning Objective: Apply robust design principles to author automated data workflows.Apply robust design principles to author automated data workflows.
What's included
3 videos1 reading1 assignment
Learners will implement production-grade Airflow workflows with retry mechanisms, SLA monitoring, and parameterization for enterprise-ready data pipeline resilience.
What's included
2 videos1 reading2 assignments1 ungraded lab
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