[NEW] Apache Flink 101 Developer Course- PyFlink Hands On !

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Big Data Landscape

2:10:59

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1. Introduction

1. Introduction.mp4

01:31

2. Course Welcome and Student Information.html

3.1 Apache Flink Introduction - Big data Landscape.pdf

3. Apache Flink Introduction - Big Data Landscape Book.html

2. Understanding Apache Flink Architecture

1. Apache Flink Application Execution Architecture.mp4

03:23

2. Flinks Architecture.mp4

04:40

3. Apache Flink - Comprehensive Overview.html

4. Flink APIs overview.mp4

06:18

5. Quiz.html

3. Big Data Processing Benchmark - Spark vs Flink

1. Spark vs Flink.mp4

03:57

2. Apache Spark vs Apache Flink.html

4. Apache Flink Installation - Configuration

1. Apache Flink Installation and Configuration A Brief Overview.html

2. Install Java 11.mp4

01:57

3. Step by step - Recap Article.html

4. Install Apache Flink.mp4

02:21

5. Stop Flink Cluster.html

6. PyFlink Requirements.html

7. Installing Python 3.10 on Ubuntu (or your desired version).html

8. Install pip ( pyFlink Requirement).html

9. Install Pyflink.mp4

01:25

10. Reading - Deploying Apache Flink on Kubernetes A Comprehensive Guide.html

11. NOTE - Unlocking Excellence.html

5. Flink Table API - Pyflink

1. PyFlink Introduction.mp4

01:13

2. Flink Scala API.html

3. Flink Table API - Introduction.mp4

01:11

4.1 code1.zip

4. Flink Table Api - First Handson program.mp4

02:52

5. NOTE - Access to All Source Code from Our Videos .html

6.1 code2.zip

6. Create Table using a List Object.mp4

02:17

7.1 code3.zip

7. Create Tables using DDL statements.mp4

03:15

8.1 code4.zip

8. Create Tables using TableDescriptor.mp4

02:42

9. Pre-Course Survey.html

10. Quiz.html

11. Assignment.html

6. PyFlink Table API - Write Queries

1. Write Table API Queries - Introduction.mp4

01:20

2.1 code5.zip

2.2 code6.zip

2. Table API aggregation query - Table API Query.mp4

03:57

3.1 code7.zip

3. Write SQL Queries.mp4

02:53

4.1 code8.zip

4. Mix the Table API and SQL- Use Table Object in SQL.mp4

02:13

5.1 code9.zip

5. Mix the Table API and SQL- Use SQL tables in Table API.mp4

02:24

6. Quiz.html

7. Assignment Integrating Table API and SQL in Apache Flink.html

7. Real World Streaming Project Real Time Streaming pipeline Handson

1. Real Time Streaming Pipeline Architecture Design.mp4

03:06

2. Handson Project Requirements.mp4

01:50

3. Data Source - API for Real Time Data.mp4

01:02

4. Extracting Real Time Data Stream from API in python.mp4

06:50

5. About Apache Kafka.mp4

02:01

6. Create Kafka Producer - Stream Data Flow.mp4

02:45

7.1 Kafka producer Project code.zip

7. Source Code - Kafka Producer.html

8. Exploring the Architecture of a Scalable Streaming Pipeline.html

9. Configure Flink to consume data from a Kafka topic as a data source pyFlink.mp4

11:32

10. About Elasticsearch & Kibana Overview.html

11. Configure Flink to write the processed data to a Elasticsearch sink pyFlink.mp4

10:24

12. Real Time Tweets Word Count with pyFlink and Kafka.mp4

21:19

13.1 Real+Time+Streaming+pipeline+Handson+code.zip

13. Complete Code Source - Flink Project.html

8. Apache Flink Real Time Streaming Concepts

1. Introduction to Stateful Stream Processing - Apache Flink.mp4

03:28

2. Flink Dataflow & Snapshots.mp4

05:20

3. Flink Data Flow and snapshots.mp4

09:33

9. Certified Apache Flink - Mastery Award Exam

1. Practice Test - Part 1.html

2. Practice Test - Part 2.html

3. Elevate Your Skills Post-Practice Test on Udemy!.html

10. More learnings

1. Reading Machine Learning with Apache Flink.html

2. Reading Gelly - Revolutionizing Graph Analytics with Apache Flink.html

3. A Heartfelt Thank You to Our Udemy Students.html

Description

From Installation to Advanced BATCH and REAL TIME Analytics Hands-On: Mastering Apache Flink | KAFKA + Pyflink STREAMING

What You'll Learn?

Introduction to Apache Flink as Big Data Processing Framework for Batch and Real Time Streaming
Flink (better than Spark) for real-time processing: Learn how to leverage Apache Flink for real-time data processing and analytics in streaming pipelines.
Apache Flink Stream processing with Pyflink
Install, configure, and utilize Flink and PyFlink effectively
Compare Flink's capabilities with Apache Spark for informed use
Master Apache Flink's architecture and real-time streaming concepts
Understand and implement the Flink Table API for efficient data processing
Create and manipulate tables using Flink Table API with various methods
Utilize Flink Table API for both batch and stream processing applications
Leverage advanced features of Flink Table API for complex data queries
Integrate Apache Kafka with Flink for real-time data ingestion and processing
Design and execute a stream processing pipeline using Flink and Kafka
Handle high-volume data streams in real-time with Kafka-Flink integration
Ingest and process streaming data with Kafka and Flink, and store results in Elasticsearch.
Implement data indexing in Elasticsearch using Flink for enhanced search capabilities
Hands-on implementation: Get hands-on experience by building a Flink Python-based solution that consumes Kafka data streams
Visualize real-time data streams with Elasticsearch and Kibana dashboards

Who is this for?

Big Data Enthusiasts: Professionals or enthusiasts interested in working with big data and real-time data processing.

Big Data Python Developers: Python developers who want to explore the world of big data and streaming data processing.

Data Engineers: Aspiring or current data engineers who want to expand their knowledge and skills in streaming data processing.

Beginners in Big Data: Individuals who are new to big data and streaming data processing but have a basic understanding of programming concepts. The course will provide a beginner-friendly introduction to building Flink streaming pipelines, helping them gain confidence and practical skills in handling real-time data.

Apache Flink Developpers

Data Engineers and Software Developers: Professionals in data engineering and software development who want to enhance their skillset in big data processing. This course is ideal for those looking to build or optimize real-time data processing pipelines using Apache Flink, Kafka, and Elasticsearch.

Aspiring Data Scientists: Individuals aiming to enter the field of data science and who are interested in the practical aspects of real-time data analytics. The course provides hands-on experience with some of the most sought-after technologies in the industry.

Academics and Students: Students and educators in computer science, data science, and related fields who seek a practical and in-depth understanding of real-time data processing systems. The course bridges the gap between academic theory and industry practice.

Big Data Hobbyists and Enthusiasts: Individuals with a keen interest in big data technologies and who enjoy exploring new tools and techniques in data processing. This course offers a structured and comprehensive learning path.

What You Need to Know?

Basic familiarity with Python programming language would be helpful

This course is designed to be beginner-friendly

You will be guided through practical exercises that focus on building an end-to-end streaming pipeline using Python

Basic Knowledge on Big Data Processing and Streaming Concepts

Basic Knowledge of SQL

Good to have Familiarity with Linux/Unix Environment

A foundational understanding of big data principles and distributed systems will be beneficial.

More details

Description
NOTE : THIS IS THE LATEST UPDATED APACHE FLINK COURSE IN THE WORLD
GOODÂ NEWS : THISÂ COURSEÂ CONTAINSÂ END-TO-ENDÂ STREAMINGÂ PROJECTÂ WITHÂ COMPLETEÂ CODE

Welcome to a transformative learning experience where mastering Apache Flink is not just a possibility, but a guarantee.
Our course stands out in the realm of Big Data processing, offering a unique blend of comprehensive concepts, hands-on experience, and an immersive end-to-end streaming project. If you're looking to elevate your skills in real-time analytics with the latest tools and techniques, you've found your match.

Are you ready to dive into the world of Apache Flink, the powerhouse of big data processing that's revolutionizing the industry? If you want to harness the full potential of this cutting-edge tool, look no further!
Apache Flink is the go-to choice for both batch and streaming data processing, offering lightning-fast performance that surpasses even the mighty Spark. Big players like Alibaba and Netflix rely on Flink for real-time stream processing, and now you can too!

What Makes Our Course Exceptional?
State-of-the-Art Curriculum: Delve into the core concepts and advanced features of Apache Flink, Kafka, and Elasticsearch. Our curriculum is meticulously crafted to ensure you grasp both the theoretical and practical aspects of real-time data processing.
Hands-On Approach: We believe in learning by doing. Each section of our course is complemented with hands-on examples and exercises. You'll not just learn but implement, giving you a real taste of what it's like to work with these powerful technologies.
End-to-End Real-Time Streaming Project: The crown jewel of our course is a capstone project where you'll build a complete real-time streaming pipeline. This project integrates Apache Flink with Kafka for data streaming and Elasticsearch for analytics, offering you a holistic learning experience.
Access to Complete and Current Code: Say goodbye to outdated examples. Our course provides you with access to the complete source code for every module. This code is regularly updated to keep pace with the latest versions and best practices in the industry.
No Outdated Content: We understand the frustration of learning from obsolete materials. Our course content is vigilantly reviewed and updated, ensuring that what you learn is relevant, current, and effective.
Course Highlights:

Introduction to Big Data & Apache Flink
In-Depth Understanding of Flink's Architecture
Benchmarking Big Data Tools: Spark vs Flink
Comprehensive Guide to Flink Installation and Configuration
Mastering Flink Table API and PyFlink
Advanced Query Writing with Table API and SQL
Building Real-Time Streaming Pipelines with Flink, Kafka, and Elasticsearch
Advanced Streaming Concepts in Flink

Why This Course?
Cutting-Edge Content: Our course is designed to keep you ahead in the fast-evolving field of Big Data and real-time analytics.
Practical Skills for Real-World Challenges: The skills you gain here are immediately applicable, preparing you for professional challenges.
Expert Instruction and Support: Learn from industry veterans and join a community where your queries and challenges are addressed with priority.
Lifetime Access and Updates: Enroll once and get lifelong access to all course materials, including future updates.
Who Should Enroll?
Aspiring and Practicing Data Engineers and Analysts
Software Developers eager to expand into Big Data
IT Professionals aiming to specialize in real-time data processing
Students and Academics seeking practical, up-to-date knowledge in Big Data Technologies
Embark on Your Journey to Mastering Real-Time Data Analytics with Apache Flink. Enroll Today and Be Part of the Data Revolution!

But what sets this course apart from the rest?
We pride ourselves on being *up-to-date and cutting-edge**. Unlike other courses that might be outdated, our course is* based on the latest Flink official documentation, version 1.17.1, in *2023**. You can trust that you're learning the most current and relevant information available.*

Are you ready to embrace the future of big data processing with Apache Flink, the 5G in the world of data frameworks? As the successor to Hadoop and Spark, Apache Flink is leading the charge in stream processing and beyond.
If Hadoop was the 2G era and Spark represented 3G, then Apache Flink is the 5G or 4G powerhouse in the realm of big data stream processing frameworks. Unlike Spark, which made do with stream processing as an add-on, Apache Flink is a genuine streaming engine. But it doesn't stop there. Flink offers the added capacity to perform batch processing, graph analysis, table operations, and even run machine learning algorithms seamlessly.
The demand for Apache Flink is soaring, and it's the latest big data technology that's quickly gaining momentum. Just as Spark once replaced Hadoop, it's foreseeable that Flink could take the lead in the near future.

In our comprehensive course, you'll embark on a journey to become a Flink expert from scratch. We'll demystify the architecture of Flink, introducing you to key components like JobManagers, TaskManagers, Tasks, Operator Chains, Task Slots, and Resources. You'll gain a deep understanding of Flink's inner workings, setting a strong foundation for your big data journey.

Our course is designed to make complex concepts crystal clear. We'll explore Flink's layered APIs, including SQL & Table API and DataStream API, ensuring you're well-versed in building and processing data streams with ease. Whether you're new to stream processing or looking to level up your skills, we've got you covered.
Here's what you'll discover:
Parallel Dataflows: Uncover the magic behind parallelism in Flink, optimizing your stream processing for maximum efficiency.
Timely Stream Processing: Master the art of timely data processing, ensuring your applications are always up-to-date with the latest insights.
Stateful Stream Processing: Learn how to manage state in your stream processing applications, opening the door to advanced real-time analytics.
Fault Tolerance via State Snapshots: Understand Flink's robust fault tolerance mechanism, utilizing state snapshots to keep your applications running smoothly, even in the face of unexpected hiccups.
By the end of this course, you'll be equipped with the skills and knowledge to leverage Apache Flink as a powerful tool for big data processing. Whether you're aiming to enhance your career prospects or tackle complex data challenges, this course is your gateway to success.
Join us on this exciting journey and unlock the potential of Apache Flink. Don't miss out â€“ enroll now and take your big data skills to the next level!

Key Words related to this Course : Apache Flink Concepts, Flink Streaming, Flink Batch Processing, Flink Data Analysis, Flink Fault Tolerance, Flink Parallelism, Flink JobManager, Flink TaskManagers, Flink DataStream API, Flink SQL & Table API, Flink State Management, Flink Data Processing Framework, Flink Dataflow Patterns, Flink Real-Time Processing, Flink Machine Learning, Flink Graph Analysis, Flink Table Operations, Flink Latest Version, Flink Hands-On Learning, Flink Coding Examples, Flink Data Consistency, Flink Time Travel, Flink Market Demand, Flink Adoption Rate, Flink Documentation, Flink Tutorials, Apache Flink vs. Spark, Flink Use Cases, Flink Big Data Solutions, Flink Certification
Who this course is for:
Big Data Enthusiasts: Professionals or enthusiasts interested in working with big data and real-time data processing.
Big Data Python Developers: Python developers who want to explore the world of big data and streaming data processing.
Data Engineers: Aspiring or current data engineers who want to expand their knowledge and skills in streaming data processing.
Beginners in Big Data: Individuals who are new to big data and streaming data processing but have a basic understanding of programming concepts. The course will provide a beginner-friendly introduction to building Flink streaming pipelines, helping them gain confidence and practical skills in handling real-time data.
Apache Flink Developpers
Data Engineers and Software Developers: Professionals in data engineering and software development who want to enhance their skillset in big data processing. This course is ideal for those looking to build or optimize real-time data processing pipelines using Apache Flink, Kafka, and Elasticsearch.
Aspiring Data Scientists: Individuals aiming to enter the field of data science and who are interested in the practical aspects of real-time data analytics. The course provides hands-on experience with some of the most sought-after technologies in the industry.
Academics and Students: Students and educators in computer science, data science, and related fields who seek a practical and in-depth understanding of real-time data processing systems. The course bridges the gap between academic theory and industry practice.
Big Data Hobbyists and Enthusiasts: Individuals with a keen interest in big data technologies and who enjoy exploring new tools and techniques in data processing. This course offers a structured and comprehensive learning path.

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Instructor's Courses

Welcome to my Udemy profile! As an experienced Big Data Engineer with a passion for data-driven solutions, I'm thrilled to share my expertise with you. With years of hands-on experience working with large-scale datasets and a deep understanding of Big Data technologies like Hadoop, Spark, Flink, Airflow, Hbase, Hive, Kafka, and more, I'm committed to helping learners like you unlock the power of Big Data.In my Udemy courses, I've carefully crafted comprehensive yet beginner-friendly content to ensure you gain practical skills and knowledge to tackle real-world Big Data challenges. Whether you're a budding data engineer, a Python developer eager to dive into the world of Big Data, or an enthusiast seeking to leverage the power of data, my courses are tailored to meet your needs.I believe in a hands-on approach, so you can expect engaging exercises and real-world examples that bridge the gap between theory and practice. I'll guide you through step-by-step implementations, empowering you to build end-to-end streaming pipelines using Python and cutting-edge tools. From data ingestion to real-time processing, storage to visualization, you'll gain mastery over the complete pipeline.Join me on this exciting journey to unlock the potential of Big Data. Let's dive deep into the world of data-driven insights and uncover the possibilities that lie within. Enroll in my courses today and embark on a transformative learning experience!

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