Apache Airflow 3 – The Complete Bootcamp [With Projects]

What you'll learn

Understand Airflow Architecture and core components - DAG Processor, Metadata DB, Scheduler, Executor, Webserver, Workers, and how they interact
You'll also build 2 end-to-end projects including AWS S3, Spark, Databricks, AWS Glue, APIs, etc. to solidify your learning and gain strong hands-on
Build industry-grade DAGs using modern TaskFlow API for complex dependencies, branching & subDAGs
Learn XCOMs and kwargs for inter-task communication and passing data between tasks in the DAGs
Master Operators and Hooks to interact with external systems like databases, APIs & cloud service
Schedule DAGs with Cron, Delta Triggers, and Event-based triggers covering real-world use cases
Monitor & troubleshoot DAGs using the Airflow UI, logs, and metrics to ensure reliability
Create connections in Airflow to securely store credentials for external systems
Implement Incremental Data Loading & Backfilling of DAGs to manage historical data
Implement error handling and retry mechanisms to ensure robust and fault-tolerant workflows
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

Requirements

Basic Python knowledge will be required.
Basic SQL knowledge will be required.
No prior knowledge in Apache Airflow is required (Will cover everything from SCRATCH)

Description

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.

Who this course is for

Anyone who wants to learn Apache Airflow and become an Airflow Developer

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