Get hands-on with Apache Airflow, the industry standard for orchestrating data and AI workflows, and learn to take your pipelines from a first draft to something you can run in production.You'll start with the fundamentals of Airflow, building your first Dags and learning how scheduling, error handling, and reporting remove the manual work from delivering data. From there, you'll implement more complex data engineering pipelines and automate them in a repeatable way.Next, you'll move to modern Airflow, authoring Dags with the TaskFlow API, scheduling them based on data using Assets and Asset Partitions, and making them reliable with retries, callbacks, and tests. You'll also build an end-to-end SQL ETL pipeline and add data quality checks directly in Airflow, so the data your pipeline produces stays trustworthy.Finally, a hands-on tutorial shows you how to orchestrate an AI workflow, turning a simple LLM prototype into a reliable, scheduled pipeline. You'll come away able to build and run pipelines that hold up in production.