The Complete Course Of Apache Airflow 2024
Published 7/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.31 GB | Duration: 7h 1mβ
Learn Apache Airflow in a Professional way. Become an expert in Data Pipelines and Workflows, from ZERO to HERO!
What you’ll learn
At the end of the course you will fully master Apache Airflow, to be able to programmatically author, schedule, and monitor complex workflows from scratch
You will be able to conduct Apache Airflow projects step by step, understanding all the logic and ending with advanced practical examples and complete projects
You will establish a foundational understanding of Apache Airflow and its primary components
You will learn to install and set up Apache Airflow using various methods and explore its web interface
You will develop skills to write, organize, and manage DAGs effectively using best practices
You will understand the different types of operators and executors to manage and execute tasks efficiently
You will master techniques for monitoring and logging to manage DAG runs and task statuses effectively
You will learn to scale Apache Airflow and configure high availability setups for production environments
You will explore advanced features of Apache Airflow and learn to integrate it with external systems
You will develop skills in testing, debugging, and deploying DAGs and tasks using best practices
You will design and implement a complex, real-world workflow using Apache Airflow, integrating all learned concepts
You will be able to practice the content learned in a practical way by following all the steps in the complete exercises and the hands-on projects
You will start with the basics and progressively carry out more complex steps until you reach an advanced level and absolute mastery at the end of the course
Requirements
Having basic notions Data Pipelines can help, but the course starts from scratch
Preparing and installing the needed environment to follow the practical sessions (if you don’t know how, don’t worry, it’s very easy, and I’ll explain it to you in the course!)
A decent computer and of course, desire to learn!
Description
Become an Apache Airflow professional and learn one of employer’s most requested skills nowadays!This comprehensive course is designed so that Data Engineers, Data Scientists, DevOps, Software Engineers, IT Professionals, Students. can learn Apache Airflow from scratch to use it in a practical and professional way. Never mind if you have no experience in the topic, you will be equally capable of understanding everything and you will finish the course with total mastery of the subject.After several years working in data engineering, we have realized that nowadays mastering Apache Airflow for efficient and maintainable orchestration of complex workflows is very necessary across diverse systems. Knowing how to use this tool can give you many job opportunities and many economic benefits, especially in the world of IT.The big problem has always been the complexity to perfectly understand Apache Airflow requires, since its absolute mastery is not easy. In this course we try to facilitate this entire learning and improvement process, so that you will be able to carry out and understand your own projects in a short time, thanks to the step-by-step, detailed and hands-on examples of every concept.With almost 7 exclusive hours of video, this comprehensive course leaves no stone unturned! It includes both practical exercises and theoretical examples to master Apache Airflow. The course will teach you how to proficiently deploy, manage, and optimize workflows, ensuring streamlined automation and robust data pipeline in a practical way, from scratch, and step by step.We will start with the setup and installation of the needed work environment on your computer, regardless of your operating system and computer.Then, we’ll cover a wide variety of topics, including:Introduction to Apache Airflow and course dynamicsMaster installing and configuring Apache AirflowCreate and organize DAGs effectivelyDifferent operators and executors to define and run tasksMonitor workflow execution and task statusesScale Airflow installations and ensure availabilityExplore advanced features and integrate with external systemsTest, debug, and deploy Airflow workflowsMastery and application of absolutely ALL the functionalities of Apache AirflowQuizzes, Practical exercises, complete projects and much more!In other words, what we want is to contribute our grain of sand and teach you all those things that we would have liked to know in our beginnings and that nobody explained to us. In this way, you can learn to build and manage a wide variety of projects and make versatile and complete use of Apache Airflow. And if that were not enough, you will get lifetime access to any class and we will be at your disposal to answer all the questions you want in the shortest possible time.Learning Apache Airflow has never been easier. What are you waiting to join?
Overview
Section 1: Introduction to Apache Airflow
Lecture 1 Welcome to the course
Lecture 2 Introduction to Apache Airflow
Lecture 3 Understanding DAGs (Directed Acyclic Graphs) and operators
Section 2: Apache Airflow Architecture
Lecture 4 Components of Apache Airflow: Scheduler, Executor, Metadata Database, Web Server
Lecture 5 Understanding the role of each component in workflow orchestration
Section 3: Installation and Setup
Lecture 6 Installing Apache Airflow using different methods (e.g., pip, Docker)-1
Lecture 7 Installing Apache Airflow using different methods (e.g., pip, Docker)-2
Lecture 8 Exploring Airflow’s web interface
Section 4: Writing and Managing DAGs
Lecture 9 Understanding DAGs in detail
Lecture 10 How to Write DAGs
Lecture 11 Best practices for organizing and managing DAG code
Lecture 12 How to Write DAGs Assignment
Section 5: Operators and Executors
Lecture 13 Understanding Executors
Lecture 14 Understanding different types of operators (BashOperator, PythonOperator, etc.)
Lecture 15 Operators and Executors Assignment
Section 6: Monitoring and Logging
Lecture 16 Monitoring DAG runs and task statuses
Lecture 17 Monitoring and Logging Assignment
Section 7: Scaling and High Availability
Lecture 18 Scaling Airflow horizontally and vertically
Lecture 19 Configuring High Availability (HA) setups for production deployments-1
Lecture 20 Configuring High Availability (HA) setups for production deployments-2
Section 8: Advanced Features and Integrations
Lecture 21 Working with sensors for external triggers and dependencies
Lecture 22 Integrating Airflow with external systems
Section 9: Testing and Debugging
Lecture 23 Writing unit tests for DAGs and tasks
Lecture 24 Deployment and Best Practices
Lecture 25 Practical Assignment
Section 10: Designing and implementing a real-world workflow using Apache Airflow
Lecture 26 Final Project-1
Lecture 27 Final Project-2
Lecture 28 Final Project-3
Lecture 29 Final Project-4
Lecture 30 Final Project-5
Lecture 31 Course Closure
Beginners who have never used Apache Airflow before,Data Engineers, Data Scientists, DevOps Engineers, Software Engineers, IT Professionals, Students. who want to learn a new way to create Directed Acyclic Graphs (DAGs),Intermediate or advanced Airflow users who want to improve their skills even more!
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