Build Data Pipelines with Apache Airflow

  • IntermediateLevel

  • 3088+Students Enrolled

  • 3 Hrs Duration

  • 5Average Rating

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About this Course

  • Learn workflow orchestration through real-world projects—from Airflow basics and DAGs to advanced scheduling and task dependencies.
  • Build, deploy, and manage ETL pipelines step by step using PythonOperators, BashOperators, cron expressions, hooks, and real case studies.
  • Understand how to write clean, reproducible tasks and explore scalable Airflow features used in modern data engineering pipelines.

Learning Outcomes

Master Airflow Basics

Learn the core concepts and architecture of Airflow.

Build ETL with DAGs

Create and manage ETL workflows using Airflow DAGs.

Implement Real Projects

Apply Airflow skills through hands-on case studies

Who Should Enroll

  • Aspiring Data Engineers: Ideal for students aiming to build strong foundations in workflow orchestration with Airflow.
  • Working Professionals: Great for analysts and developers looking to automate and manage data pipelines efficiently.
  • Career Switchers to Data Roles: Perfect for professionals transitioning into data engineering or ETL-focused job roles.

Course Curriculum

Learn the complete process of building Large Language Models for code, covering data curation, model training, fine-tuning, evaluation, and deployment strategies.

tools

  1. 1. Case Study: Story of Airflow

  2. 2. Course Outline

  3. 3. Prerequisites

  4. 4. Course Handouts

  1. 1. What Is Airflow

  2. 2. Airflow Architecture

  1. 1. Airflow Linux Installation

  2. 2. Airflow Windows Installation

  1. 1. Airflow Linux Installation

  2. 2. Airflow Windows Installation

  1. 1. What Are Dags

  2. 2. Tasks Vs Operators

  3. 3. Components Of Airflow Ui

  4. 4. Building Your First Dag Bashoperator

  5. 5. Building Your First Dag - PythonOperator

  1. 1. Problem Statement

  2. 2. Fetching Candidate Data

  3. 3. Project Dag Api Call Script-1

  4. 4. Project Dag Api Call-1

  5. 5. Understanding Cron Expressions

  6. 6. Project Dag Scheduled Api Call-1

  7. 7. Project Dag Api Call Retry-1

  8. 8. Project Dag Api Call Timeout-1

  1. 1. Project Candidate Screening

  2. 2. Dag Candidate Screening Script

  3. 3. Dag Candidate Screening

  4. 4. Project Interview Scheduling Onboarding

  5. 5. Dag Interview Scheduling Onboarding Overview

  6. 6. Dag Schedule Interview Script

  7. 7. Dag Candidate Feedback Script-1

  8. 8. Dag Candidate Onboarding Script-1

  9. 9. Dag Interview Scheduling-1

  10. 10. Airflow Hooks

  11. 11. Dag S3 Hook

  1. 1. Task Dependencies

  2. 2. What Is Branching

  3. 3. Project Branching Interviewer Data

  4. 4. Dag Branching-Interviewer Data

  5. 5. Sharing Data Between Tasks

  6. 6. Dag Conditional Task For Api Call

  1. 1. Process Data Incrementally

  2. 2. Dag Hr Reporting

  1. 1. Writing Clean And Reproducible Tasks

  2. 2. Further Possibilities In Project

Meet the instructor

Our instructor and mentors carry years of experience in data industry

company logo
Kunal Jain

Founder & CEO, Analytics Vidhya

Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- the world's 2nd largest Data Science community.

Get this Course Now

With this course you’ll get

  • 3 Hours

    Duration

  • Kunal Jain

    Instructor

  • Intermediate

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Globally recognized certificate
  • Verifiable online credential
  • Enhances professional credibility
certificate

Frequently Asked Questions

Looking for answers to other questions?

Apache Airflow is an open-source tool used for programmatically authoring, scheduling, and monitoring data workflows. It’s ideal for managing complex ETL pipelines.

DAGs (Directed Acyclic Graphs) represent workflows as a series of tasks with defined execution order. They are the backbone of Airflow scheduling.

Airflow is dynamic, code-first, and scalable—allowing for better flexibility, reusability, and monitoring compared to rigid GUI-based ETL tools.

PythonOperator, BashOperator, DummyOperator, EmailOperator, and custom operators created for specific use cases.

Yes, you will receive a certificate of completion after successfully finishing the course and assessments.

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