
Understand the operator as the task type in Airflow, using Python, Bash, or PySpark templates, and see how DAG, task instance, and operator shape workflows.
Create a project folder, set up a python virtual environment, and configure the Airflow docker compose file with postgres port mapping and load_examples false; then run docker compose up -d.
Learn to create your first Apache Airflow 3 DAG using the decorator approach, install Airflow in a virtual environment, and define tasks and dependencies in the DAGs folder.
Pull xcom data in airflow using ti.xcom_pull with the fetch data key from the fetch data task, then process and print the results.
Explore delta trigger, an event-based trigger or special schedule for DAGs when cron cannot handle frequency-based scheduling, with examples like every 10 days.
Learn to create task groups in Airflow 3 to organize related tasks, define dependencies within the group, and use collapsible boxes to simplify large DAGs for easier monitoring.
Set up the Airflow project codebase by organizing folders, copying and editing docker-compose.yaml, and preparing logs, DAGs, config, and plugins, with careful YAML indentation.
Learn to deploy a FastAPI application with docker compose, fetch data via Python requests, and understand container networking and internal dns for application programming interface calls across containers.
Explore the SQL operator in Airflow, a tool that runs SQL commands directly and requires a SQL database with a connection ID to execute queries.
Learn how hooks in Airflow connect to external systems, using the postgres hook to run sql and copy data from a csv file into a new table via connection ID.
This is a COMPLETE Apache Airflow 3 Bootcamp you need in 2026 to become a PRO Apache Airflow Developer.
Whether you're a beginner or a working professional looking to upskill, this course will guide step by step with a hands-on, practical, and engaging lectures (doodle illustrations).
GAIN STRONG HANDS-ON WITH:
Airflow Fundamentals & Architecture - Learn the fundamentals of Airflow and understand how DAG Processor, Metadata DB, Scheduler, Executor, Webserver, Workers work together to orchestrate data pipelines.
DAG Authoring - Master the modern TaskFlow API to build complex DAGs with dependencies, branching, and subDAGs for real-world data workflows. Learn XCOMs and kwargs for inter-task communication and passing data between tasks in the DAGs.
Operators & Hooks - Learn how to use built-in Operators and Hooks to interact with external systems like databases, APIs, and cloud services. Build custom connectors to integrate with any system.
Scheduling & Triggers - Schedule your DAGs using Cron, Delta Triggers, Event-based triggers, and specific time intervals to cover a wide range of real-world use cases.
Incremental Load & Backfilling - Implement incremental load strategies and backfill historical data to ensure your pipelines can handle both new and existing data effectively.
Monitoring & Troubleshooting - Use the Airflow UI, logs, and metrics to monitor your DAGs, identify issues, and troubleshoot errors to ensure reliable pipeline execution.
Security & Retries - Create connections in Airflow to securely store credentials for external systems. Implement error handling and retry mechanisms to ensure robust and fault-tolerant workflows.
Airflow Assets & Scaling - Develop Airflow Assets to build data aware pipelines and manage data dependencies effectively. Scale Airflow with multiple workers and queues to distribute workload and optimize performance.
End-to-End Projects - Additionally, build 2 real-world projects integrating AWS S3, Spark, Databricks, AWS Glue, APIs, and more to make your learning practical with real-world applications of Airflow.
WHAT MAKES THIS COURSE UNIQUE?
Super Engaging Lectures - No boring theory here! I explain every concept in a clear and beginner-friendly way using real-life examples and doodle visuals.
Deep Dive into Every Topic – I don’t just scratch the surface. You'll understand the “why” and “how” behind every feature.
Strong Hands-On Focus - You learn by doing. Each chapter includes so many practical labs to solidify your understanding and build real-world skills.
DISCLAIMER - This course is independently created and not affiliated with or endorsed by Airflow. All content is original, designed for educational purposes only. It is based on public documentation, real-world scenarios, and personal experience. All trademarks belong to their respective owners. For the most accurate and updated information, refer to the official Airflow documentation.