Learn to author, schedule and monitor data pipelines through practical examples using Apache Airflow
InstructorMarc Lamberti
Free
The curriculum provides a detailed look at the new Asset paradigm and various execution methods, including Sequential, Local, and Celery executors.
Instruction extends into creating custom Airflow providers and SQL decorators to extend platform functionality.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This instructional slide outlines a module focused on building end-to-end data pipelines, specifically detailing interactions with HDFS and Hive technologies.
This instructional slide highlights advanced workflow management concepts, specifically listing Branching, XCOMs, and SubDAGs as key features to explore.
This instructional slide features a red background with mechanical gear illustrations and white text stating 'Understand how Apache Airflow internally works'.
Learners have reported difficulties with Docker-compose files requiring manual fixes and inconsistencies in Airflow image versions.
The transition from basic concepts to advanced decorators can feel abrupt, often requiring significant external research and Python proficiency.
Some instructional links in the final section are reported as non-functional.
The content may be too advanced for those expecting a beginner-friendly introduction without prior research capabilities.