CF

Fundamentals of Apache Flink

2h 12m 35s
English
Paid

Fundamentals of Apache Flink is a 22-lesson 2 hours 12 minutes self-paced course by Zero To Mastery. This course will help you master Apache Flink from scratch and learn how to build efficient real-time data stream processing systems for real-world tasks.

Course facts

Lessons
22
Duration
2 hours 12 minutes
Level
All levels
Language
English
Updated
Instructor
Zero To Mastery
Price
Premium

This course will help you master Apache Flink from scratch and learn how to build efficient real-time data stream processing systems for real-world tasks. The material is practice-oriented and allows you to quickly transition from theory to creating working real-time pipelines.

What you will learn in the course

The program covers key concepts of Apache Flink and modern approaches to working with streaming data. After completing the course, you will confidently understand the Flink architecture and be able to apply it in real projects.

  • Basics of stream processing and distributed systems.
  • Deploying Flink in local and cloud environments.
  • Working with DataStream API and building a full-fledged real-time pipeline.
  • Mechanisms of time processing, windows, state, and late events.
  • Integration of Flink with Kafka and other data sources.
  • Optimization, monitoring, and debugging of Flink jobs in a production environment.

Practical focus of training

Each module of the course is accompanied by practical assignments that allow you to practice skills in real scenarios of processing large volumes of data.

Working with real data streams

You will create and run applications using data sources and sinks, work with event time, watermarks, and state management.

Integrations and performance

The course thoroughly examines connecting Flink to Kafka, setting up checkpoints, failure handling, and task execution optimization for high-load systems.

Who this course is for

The training is designed for listeners who want to master modern data streaming technologies and apply them in their professional activities.

  • Beginning data engineers and Big Data specialists.
  • Backend developers working with high-load systems.
  • ML engineers requiring streaming data preprocessing.
  • Anyone who wants to master Flink and learn how to create real-time pipelines.

What skills you will acquire

  • Designing real-time data processing systems.
  • Creating scalable Flink applications.
  • Understanding the intricacies of working with time and state.
  • Integrating Flink into existing data infrastructure.
  • Setting up monitoring and optimizing performance.

Conclusion

After completing the course, you will be able to confidently apply Apache Flink in real projects — from prototypes to production solutions, creating reliable and scalable data stream processing pipelines.

Additional

https://github.com/mushketyk/ztm-data-engineering/tree/main

Who teaches Fundamentals of Apache Flink? Zero To Mastery

Zero To Mastery thumbnail

Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.

The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.

The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.

What lessons are included in Fundamentals of Apache Flink?

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#1: Introduction
All Course Lessons (22)
#Lesson TitleDurationAccess
1
Introduction Demo
09:46
2
Introduction to Apache Kafka
09:46
3
[Optional] What Is a Virtualenv?
06:37
4
[Optional] What Is Docker?
11:03
5
What Is Apache Flink?
05:24
6
Flink Applications
08:11
7
Multiple Streams
03:11
8
Installing Apache Flink
05:46
9
Processing Individual Records
07:22
10
[Exercise] Stream Processing
04:02
11
[Exercise] Stream Processing - Solution
02:40
12
Time Windows
06:49
13
Keyed Windows
02:40
14
Using Time Windows
05:18
15
Watermarks
10:06
16
Advanced Window Operations
06:17
17
Stateful Stream Processing
07:50
18
Using Local State
04:42
19
[Exercise] Anomalies Detection
04:35
20
[Exercise] Anomalies Detection - Solution
03:34
21
Joining Streams
05:50
22
Let's Keep Learning Together!
01:06
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Frequently asked questions

What are the prerequisites for enrolling in this course?
The course is designed for individuals who want to learn Apache Flink, so no prior experience with Flink is required. However, familiarity with basic programming concepts and stream processing principles will be beneficial. Optional lessons on Virtualenv and Docker are provided for those unfamiliar with these tools, but they are not mandatory for understanding the main course content.
What projects will I work on during the course?
Throughout the course, you will engage in practical assignments such as building a real-time data pipeline using the DataStream API. You will work with real data streams, implement time windows, manage state, and integrate Flink with Kafka. Exercises on stream processing and anomalies detection are also included to reinforce your learning.
Who is the target audience for this course?
The course is intended for programmers and data engineers who want to master real-time data stream processing with Apache Flink. It is suitable for those looking to transition from theoretical understanding to practical application in real-world scenarios, particularly in high-load systems that require efficient data processing.
How does this course compare in depth to other Flink courses?
This course offers a practical, hands-on approach to learning Apache Flink, with a focus on real-time data stream processing. It covers fundamental concepts such as the Flink architecture, time processing, state management, and integration with Kafka. The inclusion of exercises and real-world applications provides a deeper understanding compared to courses that focus solely on theory.
What specific tools or platforms are covered in the course?
The course covers the deployment of Apache Flink in both local and cloud environments. It details the integration of Flink with Kafka and discusses other data sources. Optional lessons introduce Virtualenv and Docker, which are useful for setting up the development environment but are not required to complete the course.
What topics are not covered in this course?
The course focuses on Apache Flink and its integration with streaming data sources like Kafka. It does not cover non-streaming data processing systems or other real-time data processing frameworks outside of Flink. Advanced topics in data science or machine learning are also not part of this curriculum.
How much time should I expect to commit to this course?
With 22 lessons included, the course requires a considerable amount of time to complete, especially when accounting for practical assignments and exercises. While the exact runtime is not specified, learners should expect to dedicate several hours per week over multiple weeks to fully grasp the material and complete the exercises.