Apache Airflow: Complete Hands-On Beginner to Advanced Class
What you'll learn
- Core and Advanced Concepts in Airflow through Real-World Examples
- Architecture Components of Apache Airflow
- How to Set Up Connections to External Resources
- How to Load and Analyse Data in a Data Warehouse using Airflow
- How to Schedule PySpark jobs using Apache Airflow
- How to Extend Airflow with Custom Operators and Sensors
- How to Test Airflow DAGs and Operators
- How to Deploy Airflow Instances with Different Executors
- How to Set Up Error Tracking and Monitoring
- Intermediate Python programming knowledge
- Beginner SQL knowledge
- Beginner Docker knowledge
- Having Git, Docker and Conda (or other Virtual Environment Manager) installed on your machine
Hi there, my name is Alexandra Abbas. I’m an Apache Airflow Contributor and a Google Cloud Certified Data Engineer & Architect with over 3 years experience as a Data Engineer.
Are you struggling to learn Apache Airflow on your own? In this course I will teach you Airflow in a practical manner, with every lecture comes a full coding screencast. By the end of the course you will be able to use Airflow professionally and add Airflow to your CV.
This course includes 50 lectures and more than 4 hours of video, quizzes, coding exercises as well as 2 major real-life projects that you can add to your Github portfolio!
You will learn:
How to install and set up Airflow on your machine
Basic and advanced Airflow concepts
How to develop complex real-life data pipelines
How to interact with Google Cloud from your Airflow instance
How to extend Airflow with custom operators and sensors
How to test Airflow pipelines and operators
How to monitor your Airflow instance using Prometheus and Grafana
How to track errors with Sentry
How to set up and run Airflow in production
This course is for beginners. You do not need any previous knowledge of Apache Airflow, Data Engineering or Google Cloud. We will start right at the beginning and work our way through step by step.
You will get lifetime access to over 50 lectures plus corresponding cheat sheets, datasets and code base for the lectures!
Who this course is for:
- Data Engineers
- Data Scientists
- Python Developers Interested in Data Engineering
- Data Analysts with Python Programming Knowledge
Alexandra is a Google Cloud Certified Data Engineer & Architect and Apache Airflow Contributor.
She has experience with large-scale data science and engineering projects. She spends her time building data pipelines using Apache Airflow and Apache Beam and creating production ready Machine Learning pipelines with Tensorflow.
Alexandra was a speaker at Serverless Days London 2019 and presented at the Tensorflow London meetup.