Course Description
This intensive two-day course is designed to provide participants with a comprehensive understanding of Apache Airflow, an open-source platform to programmatically author, schedule, and monitor workflows. Through a blend of theoretical knowledge and hands-on exercises, participants will gain proficiency in designing, deploying, and managing workflows efficiently using Airflow.
What You’ll Learn?
- Understand the fundamentals of Apache Airflow architecture and components
- Learn how to create and manage workflows using Airflow DAGs (Directed Acyclic Graphs)
- Explore advanced features such as sensors, operators, and hooks
- Dive into best practices for workflow scheduling, monitoring, and error handling
- Gain insights into scalability and performance optimization techniques
- Deploy and manage Airflow in production environments
- Explore integration possibilities with other tools and technologies
Target Audience:
- Data Engineers
- Data Scientists
- DevOps Engineers
- Software Developers
- IT Professionals interested in workflow automation
Why Enroll in the Course:
- Gain practical skills in one of the leading workflow management platforms used in the industry
- Enhance your career prospects with expertise in Apache Airflow
- Learn from experienced instructors with real-world implementation experience
- Hands-on exercises and case studies for practical application of concepts
- Access to a supportive learning community and resources for continued growth
Pre-requisites:
- Basic understanding of Python programming language
- Familiarity with Linux command-line interface
- Knowledge of distributed computing concepts is beneficial but not mandatory
Lessons:
