Learn Airflow v2 in an hour

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And Ozbay

1:13:03

15 View

1 - Introduction

1 - Introduction.mp4

00:39

2 - Cheat Sheet.txt

2 - Course prerequisites please do not skip.mp4

02:29

3 - Set up.mp4

06:10

3 - files.zip

4 - Interacting with the containers.mp4

03:34

2 - Writing Workflows

5 - Fundamental concepts.mp4

07:59

6 - Creating and executing a DAG.mp4

10:49

7 - Backfills and schedule intervals.mp4

05:03

8 - Python Operator.mp4

04:55

8 - learnoperators.zip

8 - parser.zip

9 - Branch Operator.mp4

12:14

10 - Connections and hooks.mp4

05:03

11 - Postgres Operator.mp4

05:34

11 - createtablesqlsnippet.zip

12 - Completing the workflow.mp4

05:49

12 - callables.zip

12 - learnoperators.zip

3 - Next Steps

13 - Where to go from here.mp4

02:45

Description

Presented by And Ozbay

What You'll Learn?

Understand the overall Airflow system
Learn about DAGs, operators, sensors, connections, hooks, etc.
Get an introduction into advanced topics, like XCOMs, conditional execution, etc.
Do a high level review of the Apache Airflow code base
Get the ability to unblock yourself if you run into any issues running Airflow workflows

Who is this for?

Data scientists and data engineers who would like to start writing workflows in Airflow v2 quickly

What You Need to Know?

At least 8 gigabytes of memory

Familiarity with Python

More details

Description
Airflow is an Apache project, used to programmatically author, schedule and monitor workflows. It was originally developed by Airbnb and then later open-sourced. Today, many technology companies use Airflow to orchestrate their workflows.

This course is designed to get you up and running with Airflow v2 in an hour. The specific focus of the course is on teaching you the fundamentals of using Airflow rather than setting up a production environment. We will set up a sandbox environment with Airflow and PostgreSQL Servers running for you to code along and practice what you have learned. The skills you learn in this course will be transferable to your work, where a production environment is already available and maintained. Alternatively, if you are interested in using Airflow for hobby projects, the sandbox environment that you set up on your machine will likely be sufficient.

When you are taking this course, you will:
Learn the core Airflow concepts
Write an end to end workflow that takes data, cleans it up and writes into a database
Learn a number of different operators and get the hand of using operators so that you can easily incorporate new ones into your workflow
Understand how you can unblock yourself if you run into issues running your code

Who this course is for:
Data scientists and data engineers who would like to start writing workflows in Airflow v2 quickly

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Data Science

And Ozbay

Instructor's Courses

And has a PhD in Systems Science and has been in the analytics field for the last 20+ years at various capacities. He spearheaded high visibility / high impact projects working for companies like eBay, Groupon, Pinterest and Etsy, in the areas of risk management, marketing, experimentation, advertising and CRM. His expertise is in developing data products, experimentation, econometrics and machine learning.

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