inflearn logo
inflearn logo

Apache Flink with Silicon Valley Engineers

Real-time data processing is now essential, not optional! Learn to handle real-time streaming smartly with Apache Flink. Batch? Streaming? Even complex concepts can be understood easily and quickly. Hands-on practice configuration where you'll get the hang of it by directly working with Kafka and DB integration! In a world driven by data, start first with Flink.

(4.1) 11 reviews

157 learners

Level Beginner

Course period Unlimited

flink
flink
Big Data
Big Data
Data Engineering
Data Engineering
data-analysis
data-analysis
data-transformation
data-transformation
flink
flink
Big Data
Big Data
Data Engineering
Data Engineering
data-analysis
data-analysis
data-transformation
data-transformation

Reviews from Early Learners

Reviews from Early Learners

4.1

5.0

ADK123

100% enrolled

I'll need to watch Flink repeatedly 😭

5.0

동그리

97% enrolled

Following the Apache Spark course, I really enjoyed the Apache Flink course as well! I was able to understand at a glance how the concepts learned in Spark are extended to real-time in Flink, and the instructor's explanations were so clear that even complex streaming concepts became easily approachable. There were many examples that could be directly applied to practical work, which was very helpful. I'm looking forward to the next course!

5.0

백지훈

100% enrolled

I had heard of Apache Flink before but didn't know exactly what it was, and I think this course gave me a chance to build a solid foundation. Thank you for the great lecture.

What you will gain after the course

  • Conceptual Differences Between Real-time Data Streaming and Batch Processing

  • Understanding Flink's Core Components and Architecture

  • Kafka, File System, Flink Integration Practice

  • Windows, state management, checkpoints, and other features frequently used in practice

🚀 The Core of Real-time Data Processing, Introduction to Apache Flink 2.x

  • In an era of data deluge, 'real-time processing' is no longer optional—it's essential!

  • Apache Flink is the ultimate real-time data processing solution already being used by global companies like Netflix, Uber, and Alibaba.


  • 🧠 What is Flink?
    Not micro-batch, but real real-time! I'll explain Flink architecture and core concepts in an easy way.

  • Real-time vs Batch: Let's Settle This
    Let's compare the differences and pros/cons of both approaches with real examples to see which one to use in what situation.

  • 💬 Perfect Match with Kafka
    "Kafka shoots the data, and Flink processes it in real-time!" This combination is really widely used in practice.

  • 🌡 Hands-On Practice: IoT Sensor Data Average Calculation Project
    Let's create a project that calculates average temperature in real-time using actual data.
    → You'll get a clear sense of how Flink is used in real-world applications.

flink, big data, data engineering, data-analysis, data transformation

Level up with Apache Flink! Start the streaming practical course now! 💪

🙌 We recommend this for

📊 I have a lot of data, but I don't know what to do with it

Developers who want to grasp the flow of real-time data streaming from start to finish

I get Kafka, but let's go all the way to real-time processing!

You're receiving data through Kafka and want to process it in real-time

🔥 Should I seriously learn data engineering?

Python and Java basics are covered, but practical work experience is still lacking for beginner developers

🎉 Here's how you'll change after taking the course!

  • The entire flow of real-time data processing is visible


    • Receive data from Kafka, analyze it in real-time with Flink, and export the results to external systems by implementing the entire flow yourself. Now the real-time pipeline becomes a tangible structure rather than an abstract concept.

  • Event time-based processing concepts become clear

    • Event Time, Watermark, and Window concepts can be confusing at first. In this course, you'll process real data based on time and experience firsthand how time concepts affect streaming processing.

  • ✅ You'll get real-world project results that you can include in your portfolio


    • 📌 "Real-time IoT Sensor Data Analysis Dashboard"

      • Receiving Sensor Data with Kafka

      • Calculating Average Temperature with Flink

      • Output and save results in real-time

📚Here's what you'll learn

Understanding the Core Concepts and Architecture of Real-time Data Streaming

  • Apache Flink 2.x's Basic Architecture and Operating Principles

  • Differences Between Batch and Streaming Processing Methods

  • # Event Time, Window, Watermark and Other Core Concepts for Real-time Processing

  • State Management and Fault Tolerance through Checkpoints

Building a Real-World Streaming Pipeline Integrated with Kafka

  • Receiving data from Kafka → Processing in Flink → Outputting externally: Complete workflow practice

  • IoT Sensor Data Average Temperature Calculation Project

🤔 Do you have any questions?

❓ Q1. I'm hearing about Flink for the first time. Can complete beginners take this course?

A. Yes! This course is designed so that even those who have never used Flink before can follow along easily.
We'll start by slowly explaining Flink's basic structure and concepts, and guide you through hands-on practice to integrate with Kafka step by step.
We'll build a solid foundation from the basics, so don't worry!

❓ Q2. I don't know much about Kafka, will that be okay?

A. Don't worry! Kafka is also explained simply, covering only the necessary parts within the course flow.
While this isn't a course that deeply dives into Kafka itself, it's structured so you can learn the concepts and configurations needed to understand real-time data flow.
By actually working with the "Kafka + Flink combination," you can naturally understand how these two technologies connect.

❓ Q3. Can I apply what I learn from the course directly to my work?

A. Yes, it's structured with examples and hands-on exercises that can be directly applied to real work.
For instance, we'll build a project together that receives IoT sensor data and calculates average temperature in real-time. This isn't just a simple exercise—
it's a structure that can be extended and applied to log analysis, monitoring, alert systems, and more in actual work environments.
After completing the course, you'll be able to see "how I can apply this to our service."

Pre-enrollment Notes

Practice Environment

  • Operating System and Version (OS): OS type and version such as macOS, Linux, Ubuntu, etc.

  • Tool used: Docker

  • Programming Languages: Python, Java

Learning Materials

  • PDF 강의 자료(각각의 동영상 학습 자료 참고) 및 코드 자료를 제공합니다.

Prerequisites and Important Notes

  • This course is structured around hands-on practice and runs Apache Flink and Kafka in a Docker environment. Therefore, having the following foundational knowledge will help you take the course more smoothly:

    • Java's Basic Syntax and Usage

    • Python's Basic Syntax and Usage

    • (Optional) Apache Spark Basic Information

    • How to Use Docker and Docker Compose

  • If you're not familiar with Docker, I recommend my free Docker beginner course.
    👉 Go to free Docker course

  • The course explains the syntax using version 2.X, which was the latest version at the time of the course launch (different from 1.X syntax)

  • If you have any questions or don't understand something during the class, please feel free to leave a comment anytime!
    I'm currently living on the West Coast of the United States, so please understand that my responses might be slightly delayed due to the time difference.
    I'll help you as quickly and accurately as possible 😊

Recommended for
these people

Who is this course right for?

  • Backend developers who want to work with real-time data processing such as logs, traffic, and sensor data

  • Data engineers who want to introduce streaming-based technologies like Flink and Kafka into practical work

  • Someone who is on a team/company looking to transition from batch processing-centered data pipelines to streaming

  • A developer who has used Spark but wants to experience real real-time processing

  • Someone interested in cloud-based real-time analytics systems

Need to know before starting?

  • Java Basic Syntax

  • Basic concepts of Kafka and message queues

  • Linux basic commands and Docker usage experience (optional)

Hello
This is altoformula

21,068

Learners

1,065

Reviews

339

Answers

4.8

Rating

29

Courses

Are you going to finish in Korea? Penetrate the global market with English! 🌍🚀

Hello. I majored in Computer Science (EECS) at UC Berkeley 💻, have worked as a software engineer in Silicon Valley for over 15 years, and am currently a Staff Software Engineer working with Big Data and DevOps at a Big Tech headquarters in Silicon Valley.

  • 🧭 I would now like to share the technologies and know-how I learned firsthand at the forefront of innovation in Silicon Valley with all of you through online lectures.

  • 🚀 Join me, having learned and grown at the forefront of technological innovation, and develop the skills to compete on the global stage!

  • 🫡 I may not be the smartest, but I want to emphasize that you can achieve anything if you stay consistent and never give up. I will always be by your side, supporting you with great resources.

 

More

Reviews

All

11 reviews

4.1

11 reviews

  • ctk03277540님의 프로필 이미지
    ctk03277540

    Reviews 1

    Average Rating 5.0

    5

    31% enrolled

    • altoformula
      Instructor

      Hello ctk0327, Thank you so much for taking the time to leave a great review.

  • sihoonylee5890님의 프로필 이미지
    sihoonylee5890

    Reviews 3

    Average Rating 5.0

    5

    31% enrolled

    • altoformula
      Instructor

      Hello sihoony.lee, Thank you so much for taking the time to leave such a wonderful review.

  • seungjoonl8216680님의 프로필 이미지
    seungjoonl8216680

    Reviews 2

    Average Rating 5.0

    5

    97% enrolled

    Following the Apache Spark course, I really enjoyed the Apache Flink course as well! I was able to understand at a glance how the concepts learned in Spark are extended to real-time in Flink, and the instructor's explanations were so clear that even complex streaming concepts became easily approachable. There were many examples that could be directly applied to practical work, which was very helpful. I'm looking forward to the next course!

    • altoformula
      Instructor

      Hello Donggeuri, I'm glad to hear that you took the Flink course following Spark, and that it was helpful to you as well. Thank you for taking the time to leave such a nice review.

  • lzservice149004님의 프로필 이미지
    lzservice149004

    Reviews 2

    Average Rating 5.0

    5

    31% enrolled

    • altoformula
      Instructor

      Hello, Kim Lezhin. Thank you for taking the time to leave such a great review! Wow~ are you moving straight on to studying Flink right after Spark? I'm sure you'll achieve great results!

  • abcd123123님의 프로필 이미지
    abcd123123

    Reviews 329

    Average Rating 5.0

    5

    100% enrolled

    I'll need to watch Flink repeatedly 😭

    • altoformula
      Instructor

      Hello ADK123, The official Flink site has documentation all over the place, so it was quite challenging to create. I'll upload supplementary lectures soon.

altoformula's other courses

Check out other courses by the instructor!

Similar courses

Explore other courses in the same field!

$34.10