Data Science

Data Engineering

Airflow Basics from a Silicon Valley Data Leader

Name: Airflow Basics from a Silicon Valley Data Leader
Price: 132000 KRW

With the advent of the AI era, building data pipelines has become a core competency that determines a company's competitiveness. Learn how to build efficient data pipelines using Airflow, the most widely used tool, directly from a Silicon Valley expert (formerly Head of the Data Team at Udemy, currently a professor in the Data Masters program at San Jose State University) with practical experience and extensive lecturing experience.

(5.0) 5 reviews

136 learners

keeyonghan9539

실습 중심

데이터파이프라인

실리콘밸리

airflow

snowflake

SQL

Python

What you will learn!

Building a data pipeline based on Airflow, Snowflake, and Docker
Practical SQL and Python skills that can be immediately applied in real-world data work.

Airflow automates complex data flows and enables accurate and reliable data collection through flexible scheduling and task management . Snowflake is a powerful cloud-based data warehouse that can quickly process and scale large amounts of data, supporting stable data operations in various business environments.

In this course, you will learn how to design and operate efficient data pipelines by combining Airflow’s workflow automation capabilities with Snowflake’s scalability and performance . You will learn the core data engineering skills that connect data collection, processing, storage, and utilization into a single flow without complex infrastructure setup.

After class

Learn about the mission of a data organization and the role of data engineering.
You will learn about data warehouses and data pipelines that make up data infrastructure.
- In this process, you can add a data warehouse called Snowflake to your skillset.
- Learn best practices that will really help you build and operate data pipelines.
You can create various data pipelines based on Airflow, the most popular data pipeline creation/operation framework.
- You will also learn advanced concepts like full updates, incremental updates, backfill, monitoring, etc.
As a data worker, you will gain hands-on experience in how Python and SQL are used to create data pipelines, which will enhance your capabilities.

Hello. I am Ki-Yong Han, a data expert in Silicon Valley with 30 years of experience. After starting my career at Samsung Electronics, I left for Silicon Valley at the age of 31. I have built data teams at organizations such as Udemy (listed on NASDAQ in 2021) and Polyvore (acquired by Yahoo in 2015), and have provided data consulting to various Silicon Valley and Korean companies. Based on this, and my experience teaching master's students at San Jose State University, which boasts the highest employment rate in Silicon Valley , I will share essential skills for data scientists.

Recommended for
these people

Who is this course right for?

People who work as data engineers or want to work as data engineers
People who work with or want to work with data-related pipelines
Someone curious about data-related work/projects

Need to know before starting?

Python (Beginner)
SQL (Beginner)

Hello
This is

850

Learners

Reviews

Answers

4.9

Rating

Courses

컴퓨터 공학 석사 후 삼성전자에서 시작된 커리어가 친구덕에 실리콘밸리로 이어져 지난 29년간 13개의 다양한 스테이지의 회사를 다녔습니다 (창업, 대기업들, 다수의 스타트업들).

야후: 엔지니어링 디렉터로 검색엔진 개발.
유데미. 데이터팀을 처음 만들어 30명까지 성장. 2021년 10월에 나스닥 상장
삼성전자
...

중간에 11개월 쉬어보기도 했고 본의 아니게 엔젤투자자(Chartmetric, Goodtime.io, Select Star, EO, 비지니스 캔버스, ...), 어드바이저(몰로코, 블라인드, 월급쟁이부자들, ...), 컨설팅(SK텔레콤, 현대카드, 이마트 등등) 등의 역할을 하면서 나만의 브랜드를 만들었습니다. 실패를 실패가 아닌 교훈으로 보는 긍정의 힘과 꾸준함이라는 복리의 힘을 믿습니다.

https://www.linkedin.com/in/keeyonghan/

유투브 채널

월급쟁이부자들 강의

Curriculum

All

68 lectures ∙ (11hr 58min)

Course Materials:

Lecture resources

Section 1. Course Introduction

2 lectures ∙ (14min)

1. Instructor Profile
05:13
2. Course Introduction
09:23

Section 2. Introduction to Data Team and Data Engineering

5 lectures ∙ (59min)

3. Data Team's Role Introduction
10:14
4. Introduction to Data Infrastructure
15:37
5. Data Engineer's Role
16:22
6. Introduction to Data Pipeline
12:38
7. Data System Example
05:02

Section 3. Snowflake Introduction and Setup

4 lectures ∙ (42min)

8. Snowflake Introduction
15:03
9. Run Snowflake Free Trial
06:21
10. Snowflake Intro
13:58
11. Snowflake Environment Hands-on
06:45

Section 4. Data Pipeline Practice

6 lectures ∙ (1hr 6min)

Section 5. Airflow: Data Pipeline Framework

2 lectures ∙ (17min)

Section 6. Docker based Airflow installation

7 lectures ∙ (1hr 6min)

Section 7. A taste of Airflow programming

16 lectures ∙ (2hr 59min)

Section 8. Airflow Basic Programming

9 lectures ∙ (1hr 41min)

Section 9. Advanced Airflow Programming

14 lectures ∙ (2hr 37min)

Section 10. Wrap-up and Next Steps

3 lectures ∙ (12min)

Published:

Last updated:

Reviews

All

5 reviews

5.0

5 reviews

horongt
Reviews 1
∙
Average Rating 5.0
5
100% enrolled
I've finally completed the course!! I was able to gain a lot technically, but the overall concepts of data engineering that the instructor took the time to explain were really helpful (content from Section 2, the future of data engineering). Through this, I was able to gain great insights into how to design pipelines and what technology stack to choose. Also, I liked that the instructor mentioned the concerns that data engineers should have from time to time during the lecture. In addition, the lecture itself was created to allow you to learn practical tips and theoretical parts in a balanced way, so I liked the part where they tell you exactly what you need to know and leave the rest to the person studying. Thank you for the great lecture!!
- keeyonghan9539
  Instructor
  Thank you for the kind review. I also have an SQL course created from a data analysis/utilization perspective. I'm planning to release a course related to Spark by early April, so please check that out later.
- horongt
  Okay!! I can listen to the SQL lecture while waiting for the Spark lecture!
dataarchitect0
Reviews 6
∙
Average Rating 4.2
5
100% enrolled
emfoa230542
Reviews 5
∙
Average Rating 5.0
5
60% enrolled
mscsy01049265
Reviews 2
∙
Average Rating 4.5
5
33% enrolled
pst54016539
Reviews 1
∙
Average Rating 5.0
5
31% enrolled

$102.30

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