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Free Download Apache Airflow Masterclass Build Real-World Projects
Published 1/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.62 GB | Duration: 8h 9m
Understand Apache Airflow deeply, design production workflows, and implement a real end-to-end analytics pipeline
What you'll learn
Understand Apache Airflow from beginner to production level.
Master DAGs, Tasks, Operators, Hooks, Sensors, and XCom.
Learn Airflow architecture: Scheduler, Webserver, Executors, Workers, and Metadata DB.
Write DAGs using the modern TaskFlow API with real demos.
Handle scheduling, retries, logging, monitoring, and production best practices.
Implement Task Groups, Dynamic Task Mapping, and dependency management.
Build a fully automated end-to-end Airflow pipeline using live APIs.
Apply Medallion Architecture: Bronze → Silver → Gold data layers.
Process incremental data, load into databases, and create BI-ready datasets.
Think and work like a professional data engineer in real-world projects.
Requirements
Basic knowledge of Python programming.
Familiarity with command-line tools is helpful but not mandatory.
Understanding of databases or SQL is a plus.
A computer capable of running Docker and Python locally.
Willingness to follow along with live coding exercises.
No prior Airflow experience is required.
Access to a code editor like VS Code.
Description
Apache Airflow is one of the most in-demand tools in modern data engineering, analytics engineering, and backend data platforms. This course is a complete, production-focused Apache Airflow masterclass, designed to take you from absolute beginner to confident, real-world Airflow user.This is not a short tutorial or a surface-level walkthrough. You will first learn Apache Airflow A-to-Z, understanding how it actually works under the hood, and then you will apply that knowledge by building a full end-to-end data engineering project using real-world data workflows.Part 1: Apache Airflow Full Course (Beginner to Advanced)In the first part of the course, we start from scratch and gradually move to advanced and production-ready concepts. Each lecture is clearly structured and mapped to real-world usage.You will learn:What Apache Airflow is, why it is used, and when it should or should not be usedCore building blocks: DAGs, Tasks, Operators, Hooks, Sensors, and XComComplete Airflow architecture explained visually, including Scheduler, Webserver, Executor, Workers, and Metadata DatabaseDifferent Airflow executors (Local, Celery, Kubernetes) and how to choose the right oneInstalling and running Apache Airflow using Docker and local setupsNavigating and using the Airflow UI effectivelyWriting DAGs using the modern TaskFlow APIDeep dive into operators with real demos (Python, Bash, Cloud, and Sensors)Variables, Connections, Secrets, and configuration best practicesXCom internals, common mistakes, and anti-patternsScheduling concepts including cron syntax, timetables, catchup, and backfillTask Groups and Dynamic Task Mapping with hands-on examplesError handling, retries, logging, monitoring, and production best practicesBy the end of this section, you will understand Airflow like a working data engineer, not just someone copying DAG examples.Part 2: End-to-End Real-World Data Engineering ProjectIn the second part of the course, we build a complete, real-world data engineering project using Apache Airflow.You will build an automated pipeline that
ulls live flight operations data from external APIsImplements Medallion Architecture:Bronze layer for raw ingestionSilver layer for cleaned and normalized dataGold layer for analytics-ready KPIsProcesses data in time-windowed, incremental batchesLoads analytics data into a cloud data warehouseHandles retries, failures, dependencies, and reruns safelyProduces analytics-ready datasets suitable for dashboardsThis project focuses on patterns, orchestration, and analytics, exactly how real data engineering teams work.Who This Course Is ForBeginners who want to learn Apache Airflow properly from scratchData Analysts moving toward Data Engineering rolesData Engineers preparing for real projects or interviewsAnalytics Engineers working with orchestration toolsAnyone who wants production-level Airflow knowledge, not just theoryAfter Completing This Course, You Will Be Able ToDesign and build production-ready Airflow pipelinesUnderstand Airflow architecture and executor choices confidentlyWrite clean, maintainable DAGs using modern best practicesBuild end-to-end data pipelines using real-world APIs and workflowsThink like a professional data engineer, not a tutorial followerThis course is built with a practical, real-world mindset and is ideal for anyone serious about mastering Apache Airflow beyond.Beginners who want to learn Apache Airflow from scratch.,Data Analysts looking to move into Data Engineering roles.,Aspiring or junior Data Engineers aiming for production projects.,Analytics Engineers who want to master workflow orchestration.,Backend Engineers interested in building data pipelines.,Professionals preparing for Airflow-focused interviews.,Anyone seeking hands-on experience with real-world pipelines.,Anyone serious about becoming a confident, real-world data engineer.
Homepage
Code:
https://www.udemy.com/course/apache-airflow-masterclass-build-real-world-projects/
Code:
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