AWS(Amazon Web Service) 입문자를 위한 강의
Sungmin Kim
요즈음 회사 및 다양한 프로젝트에서 종종 사용되는 AWS 서비스들의 핵심 이론을 배우며 뿐만 아니라 함께 따라하는 실습을 통하여 AWS를 온전히 내것으로 만들자!
Beginner
AWS, cloud-computing, cloud-platform
Lecture for AWS(Amazon Web Service) practice
Do you still feel like something is lacking even after taking all the AWS beginner, intermediate/advanced courses? The AWS practical course is just for you.
What you will learn!
Apache Airflow
AWS Batch
AWS ECR
AWS Athena
AWS Glue
Practical! The definitive guide to AWS applications.
Are you wondering how to use AWS in your work?
🤔 I finished the AWS beginner/intermediate advanced course, but I feel like I'm still missing 1%.
😎 I'm looking to get promoted at my company through the AWS Showcase.
😀 I want to build various pipelines using resources provided by AWS.
🥺 I want to experience various use cases of AWS.
🤓 I want to dive deeper into the world of the cloud.
👉 The final stop in the AWS series! We offer solutions to your concerns.
This practical AWS course wouldn't have been possible without the support of all of you who love and encourage AWS beginners , intermediate users, and advanced users . It's no exaggeration to say that this course was created thanks to your enthusiastic support and encouragement.
This course is for those who want to quickly apply AWS in real-world situations.
This course is designed to provide indirect experience with how engineers in the field use AWS to build ETL pipelines, Docker containers, and Airflow schedulers. As the title suggests, the course focuses on hands-on practice , minimizing conceptual explanation.
Each section lasts from 30 minutes to an hour. We aim to deliver the essential content in a concise, concise manner, stripping away all unnecessary details.
I highly recommend this course to anyone who wants to quickly learn and use AWS, or to anyone who wants to delve deeper into the cloud by taking an introductory course on AWS.
Provides solutions to exceptional situations that may arise in practice.
One area where I put a lot of thought into developing the course was the Troubleshooting section . My AWS environment (operating system, configuration, etc.) isn't always the same as yours. Therefore, even if things run smoothly for me, I expect you'll encounter errors. While it's impossible to explain every single error, I've put a lot of thought into compiling common errors and figuring out how you can troubleshoot them yourself. That's why I created this section.
When creating a lecture, I think, "I'm running it fine, but won't other people get this error?" and I organize the most likely exceptions and suggest solutions to them.
So, after learning...
- ✅ You can use AWS freely.
- ✅ You will get a sense of what resources are available, when, where, and how.
- ✅ You will also gain the ability to weigh the pros and cons of each situation.
- ✅ Increase your understanding of the cloud.
The final stop in Simon Kim's AWS series
This course consists of 90% hands-on practice and 10% theory . Therefore, the prerequisite knowledge is for AWS beginners . The intermediate/advanced lectures are optional, and you can watch them alongside the practical lectures.
This course, "Practical AWS," marks the final stop in the AWS series. Completing the Practical AWS course doesn't guarantee a complete understanding of AWS. However, I'm confident it will be of great help as you continue to use AWS and learn new technologies.
Check out the series player progression.
Preview learning content
1. AWS and Airflow Meet
Can Airflow run on AWS? Yes. By using AWS and Airflow together, you can build more diverse pipelines with the help of AWS resources.
(1) After creating an instance, install the packages required to run Airflow.
(2) Create an Airflow database and create a user.
(3) Run the Airflow DAG.
2. AWS Batch & ECR
This section will provide a hands-on experience creating batch jobs and queues and running images pushed to ECR. AWS Batch wasn't covered in the beginner, intermediate, and advanced courses, so this section provides a brief introduction.
(1) Create an ECR repository to store Docker images.
(2) Create a Docker image and push the image to the ECR repo.
(3) Create a batch job and queue and run the job.
3. ETL pipeline
Let's build a simple ETL pipeline using AWS resources (S3, Glue, Athena).
(1) Create a bucket to store raw data and create an Athena database to store the data.
(2) Create a Glue Crawler to extract raw data.
(3) Data goes through a verification process in Athena.
Q&A 💬
Q. Why should I take this course?
Cloud computing is now being discussed and used in a wide range of fields, not just the IT industry. Cloud infrastructure is now inseparable from our daily lives. Living in the era of big data, we produce, process, and analyze vast amounts of data every day. This is something humans simply cannot accomplish. We need the help of the cloud. AWS is here to fulfill this role.
This AWS practical course introduces several architectures frequently used in real-world applications and is structured so that you can follow along and practice. As you follow the exercises, we encourage you to ask yourself why certain resources are being used and whether there are better ways to do things. There's no right answer in the cloud; there are only better ways. You must explore and discover the best approach within your given environment. This course will help you do just that.
Q. Can non-majors also take the course?
Of course. Even if you're not a computer science major, you can still take this course if you have experience with the AWS cloud.
Please check before taking the class 📢
OS and tools for practice
- You can take the course on Windows/macOS.
- We recommend that you take the course after completing the AWS account creation.
Learning Materials
- Text files and Python code files that organize commands used during practice are provided as learning materials.
- Useful links to read before and after class can be found on the lecture bulletin board.
💡 Player Knowledge and Precautions
- This course is designed for practical application and is not suitable for AWS beginners. If you have no experience with AWS or the cloud, we strongly recommend taking the AWS Beginners series first. (You can also take this course in conjunction with the AWS Intermediate/Advanced courses .)
- You can download and use the files attached to the class to follow the practical exercises.
- If you copy the lecture content, please indicate the source.
Recommended for
these people
Who is this course right for?
Those who have completed AWS beginner, intermediate/advanced courses
Anyone who wants to build a pipeline using various AWS resources
Anyone who wants to experience various use cases of AWS
Need to know before starting?
Python
Cloud Basics
AWS
5,980
Learners
295
Reviews
156
Answers
4.7
Rating
5
Courses
안녕하세요. 저는 학부와 석사를 미국에서 나왔으며 전공은 각각 Computer Science, Data Science를 공부하였습니다. 현재 저는 Healthcare쪽 회사의 데이터 엔지니어로 일하고 있습니다. 매일 제가 하는 일을 간단하게 말씀드리자면; AWS와 Airflow를 사용하여 매일 데이터를 불러와 ETL과정을 거치며, 데이터가 잘 들어오는지 모니터링하면서 문제점 혹은 개선의 여지가 필요한 경우 프로그램을 구현하는 일을 하고 있습니다. 데이터 모니터링은 주로 AWS의 CloudWatch와 Splunk라는 프로그램을 사용하고 있습니다.현재 제가 회사에서 사용하고 있는 기술들은 Python, AWS, SQL 등등이며 최근에는 GCP로 Migration하고 있는 추이이며 AWS와 GCP를 동시에 접하고 있습니다.
2022년에는 회사에서 거의 80%의 데이터 및 파이프라인이 GCP로 Migration을 마쳤으며 Bigquery & GCS & GKE쪽을 심오하게 다루고 있습니다. 물론 Docker Container & Terraform사용으로 전반적인 IaC 작업도 병행해서 진행하고 있습니다.
데이터 엔지니어로 일하면서 가장 크게 느낀점은 다음과 같습니다. 매일 새로운 기술들의 등장으로 인해 지금 내가 사용하고 있는 기술들이 과연 obsolete해질까? 그렇다면 그 이유는 무엇인가? 정말 그 기술이 이걸로 대처될 수 있는가? 단점은 없는 것인가? 그렇습니다. 저 모든 질문들에 대한 답변을 찾는것은 매우 힘들어 보입니다. 그러나 그 과정을 겪으면서 한가지 공통점이 보였습니다. 깊게 들어가보면 거의 대동소이 하다는 것입니다. 다시 말해 하나를 제대로 파헤친다면 다른 기술을 배우는 것은 많이 용이해진다는 것이죠. 저는 이런 메카니즘을 강의에서도 종종 언급을 하고 싶습니다. 여러분들과 함께 제가 현재 가지고 있는 모든 지식들을 공유하고 싶습니다. 여러분들의 길잡이가 될 수 있도록 최선을 다하겠습니다.
저 사이먼킴은 여러분들께 재미있고 이해하기 쉬운 강의를 선보일꺼에요. 여러분들과 끊임없이 소통하면서 더 나은 사람이 될 것을 약속드리구요. 여러분들의 실력이 향상되는것을 지켜보는 것은 저의 큰 행복입니다.
집필저서: 업무에 바로 쓰는 AWS 입문
Curriculum
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17 lectures ∙ (1hr 42min)
Course Materials:
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Published:
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3 reviews
$37.40
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