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Apache Airflow with Silicon Valley Engineers

You will learn Apache Airflow, the most widely used Orchestrator for creating software data pipelines.

(4.6) 43 reviews

551 learners

  • altoformula
3시간 만에 완강할 수 있는 강의 ⏰
빅데이터
데이터 엔지니어링
apache-airflow
docker
airflow
Big Data
Data Engineering
Python

Reviews from Early Learners

What you will learn!

  • Build a data pipeline

  • Apache Airflow

  • Introduction to Apache Spark

  • Introducing MinIO

  • TaskFlow API

  • Slack Integration

Airflow, an essential tool for data pipelines
Learn from Silicon Valley developers! 🔥

Modern data workflow management,
With Apache Airflow 📌

The most used workflow management tool in the field: Apache Airflow

Learn the simple setup and usage of Airflow. We'll guide you through creating your first data workflow.

Leave complex concepts behind and dive into the fascinating world of Airflow!

As data analysis and processing tasks become more complex , issues such as job scheduling, dependency management, and error handling become more important. To effectively address these challenges, Airflow is one of the core tools of choice for many organizations.

This lecture is a lecture prepared in advance for those who are new to Airflow. Apache Airflow, which is popular in Silicon Valley. I will help you get started in a simple and easy way.

Why should you learn Apache Airflow?

Automated workflow management

Airflow provides powerful scheduling capabilities to automatically run and manage tasks over time. You can plan and execute data processing tasks more efficiently.

Dependency Management

Complex data workflows require precise management of dependencies between tasks. Airflow provides the ability to clearly define dependencies between tasks and specify the order of tasks.

Powerful monitoring and notifications

You can monitor the progress of your jobs through the Airflow dashboard while your jobs are running. You can also set up alerts to respond quickly if your jobs fail or encounter issues.

Scalability and flexibility

Airflow supports a variety of plugins and libraries. It can integrate with various data stores, job execution environments, and notification mechanisms. Build custom workflows to fit your needs.

Community and Ecosystem

Airflow has a vibrant community and rich ecosystem, so there are a lot of great resources to help you troubleshoot.


Lecture Features ✨

✅ Easy to understand without difficult concepts! Explains what Airflow is and why it is needed through analogies and examples .

A hands-on course that follows the actual Airflow usage process and creates a simple data workflow!

If you have any questions or do not understand anything during the lecture, please feel free to ask questions at any time. Learn with Q&A !


What you'll learn 📚

  • All lecture materials are in English. The lectures themselves are conducted in Korean and are designed to facilitate future overseas employment.
  • We provide PDF lecture materials and Github code.
Cloud Software Architecture Overview
Introduction to Data Pipeline Orchestrator
Introduction to Apache Airflow
Introduction to the key components of Apache Airflow
Detailed introduction of each component
Detailed analysis of the code

We will share with you the know-how of current Silicon Valley engineers!

I am a current software engineer who runs YouTube's " American Engineer " and Brunch's " Silicon Valley News and Life ." I graduated from the University of California, Berkeley EECS and am currently working on big data at the headquarters of a global big tech company in Silicon Valley. I would like to share the know-how I have learned from my actual work with many people. 🙂


If you are this type of person
Get started right now.

💡

Data Engineer

Automate and schedule data workflows to maintain data quality and consistency .

💡

Data Analyst

Try handling tasks like regular data updates or model retraining .

💡

Data Scientist

Efficiently manage your data science process by automating model training, evaluation, batch predictions, and more .

💡

system administrator

It can increase transparency and reliability of work execution.

💡

Data Engineering and Development Team

You can implement various automated tasks such as ETL (Extract, Transform, Load) tasks and API calls .

💡

Project Manager

You can effectively adjust your project schedule by setting task dependencies, priorities, expected execution times, etc.


Expected Questions Q&A 💬

Q. Why should I learn Apache Airflow?

Apache Airflow is a data workflow management tool used to automate, schedule, and monitor data pipelines. It can efficiently manage data workflows for various roles such as data engineers, data scientists, and system administrators.

In the latter half of the lecture, you will learn how to integrate with big data technology (Apache Spark), which will be of great help to data engineers who manage many pipelines.

Q. Is this a lecture that non-majors can also take?

If you are not a major but know the basics of Python and want to improve the efficiency of your data or task scheduling workflow, this will be of great help.

If you are new to Python, learn the basics of Python through YouTube or take the lecture below first! Even if you only watch the basics, you will have no trouble following the entire lecture.

Q. Is there anything I need to prepare before attending the lecture?

Since the code is written in Python, there will be no basic Python lectures. Also, there will be practical training using Docker, so it will be easier to understand if you have basic knowledge of Docker.


Things to note before taking the class 📢

Practice environment

  • Operating System and Version (OS)
    • The course will be taught on MacOS, but you can follow the exercises on any operating system that has Python (Airflow itself is a Python library).
  • Tools to use
    • Python 3.7+
    • Airflow is Apache licensed, so it's free.
  • PC specifications
    • CPU: 2 cores or more
    • Memory: 4GB or more
    • Disk: 10GB or more

Player Knowledge and Notes

  • Basic knowledge of Python and Docker is required, and the environment for this lecture is set up with Docker. If you want to know more about Docker, I recommend you refer to my free Docker lecture . Lecture link: [ https://inf.run/8eFCL ]
  • If you have any questions, please feel free to ask. However, since I am located in the western United States, it may take some time for me to respond.

Recommended for
these people

Who is this course right for?

  • Data Engineer

  • If you want to become a data engineer

Need to know before starting?

  • Python

Hello
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10,547

Learners

716

Reviews

307

Answers

4.8

Rating

25

Courses

한국에서 끝낼 거야? 영어로 세계 시장을 뚫어라! 🌍🚀

안녕하세요. UC Berkeley에서 💻 컴퓨터 공학(EECS)을 전공하고, 실리콘 밸리에서 15년 이상을 소프트웨어 엔지니어로 일해왔으며, 현재는 실리콘밸리 빅테크 본사에서 빅데이터와 DevOps를 다루는 Staff Software Engineer로 있습니다.

  • 🧭 실리콘 밸리의 혁신 현장에서 직접 배운 기술과 노하우를 온라인 강의를 통해 이제 여러분과 함께 나누고자 합니다.

  • 🚀 기술 혁신의 최전선에서 배우고 성장해 온 저와 함께, 여러분도 글로벌 무대에서 경쟁할 수 있는 역량을 키워보세요!

  • 🫡 똑똑하지는 않지만, 포기하지 않고 꾸준히 하면 뭐든지 이룰수 있다는 점을 꼭 말씀드리고 싶습니다. 항상 좋은 자료로 옆에서 도움을 드리겠습니다

 

Curriculum

All

32 lectures ∙ (4hr 8min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

43 reviews

4.6

43 reviews

  • JINYEONG LEE님의 프로필 이미지
    JINYEONG LEE

    Reviews 1

    Average Rating 5.0

    5

    31% enrolled

    • 미쿡엔지니어
      Instructor

      안녕하세요 JINYEONG LEE님, 시간내서 좋은 평가해주셔서 감사합니다.

  • pdy님의 프로필 이미지
    pdy

    Reviews 18

    Average Rating 5.0

    5

    31% enrolled

    좋습니다

    • 안녕하세요 pdy님, 시간내서 좋은 평가해주셔서 감사합니다.

  • dscover.skku님의 프로필 이미지
    dscover.skku

    Reviews 2

    Average Rating 5.0

    5

    100% enrolled

    • 안녕하세요 dscover.skku님, 시간내서 좋은 리뷰 주셔서 감사합니다.

  • 이관형님의 프로필 이미지
    이관형

    Reviews 1

    Average Rating 5.0

    5

    63% enrolled

    • 안녕하세요 이관형님, 시간내서 좋은 평가해주셔서 감사합니다.

  • Ophelie님의 프로필 이미지
    Ophelie

    Reviews 2

    Average Rating 5.0

    5

    31% enrolled

    이전에 spark 강의 듣고 이어 듣고 있는데, 이론과 실습까지 알찹니다. 대학 때 잘 가르쳐주시는 교수님 강의 듣는 것 같아요, 유용한 컨텐츠 감사합니다.

    • 안녕하세요 Ophelie님, 시간내서 좋은 리뷰 정말 감사드립니다. 뿌듯하네요!

$51.70

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