Apache Flink & Kafka End-to-end Streaming Project Hands-on
What you'll learn
- Kafka fundamentals: Master the key concepts and functionalities of Apache Kafka for efficient data ingestion and 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.
- Elasticsearch for indexing and search: Explore the capabilities of Elasticsearch for indexing and querying large volumes of streaming data in real time.
- Visualization with Kibana: Use Kibana to create interactive visualizations and dashboards that provide insights into your streaming data pipeline.
- Integrating Kafka and HDFS: Learn how to integrate Kafka with HDFS using Python to store streaming data efficiently and reliably.
- Hands-on implementation: Get hands-on experience by building a Python-based solution that consumes Kafka data streams and stores them in HDFS
- PyFlink for real-time processing: Utilize PyFlink for real-time data processing.
- Pydoop for HDFS integration: Integrate HDFS with Python using Pydoop.
- Kafka-Python for Kafka integration: Connect to Kafka and process streaming data using Kafka-Python.
- Apache Flink Stream processing with Pyflink
- End to End Real World Big Data Project : Stream processing pipeline
- This course is designed to be beginner-friendly
- Basic familiarity with Python programming language would be helpful
- You will be guided through practical exercises that focus on building an end-to-end streaming pipeline using Python
- Basic Knowledge on Kafka, Flink, Hadoop, Elasticsearch and Kibana
This is the only updated Handson "Apache Flink" Course in the World !
This is a practical Apache Flink Handson Course (not thorical) with complete real world end-to-end project
Say goodbye to the frustration of searching for code snippets or outdated examples!
Our course ensures you have everything you need to succeed. We believe in the power of hands-on learning, and that's why we provide you with comprehensive handson with code samples and examples.
NB: This is not a theorical course, It's a practical big data hands on course
For Non-Python developer's help, All Flink & Kakfa Python codes are explained line by line in such a way that even a non -technical person can understand.
Unlock the power of real-time data processing and revolutionize your data engineering skills with our comprehensive practical course, "Build End-to-End Streaming Pipeline: Python Big Data Hands-On."
Designed for data engineers, Python developers, and big data enthusiasts, this course takes you on a practical journey to master the art of building streaming data pipelines using Python.
Through hands-on exercises and real-world examples, you'll gain a solid understanding of streaming data processing concepts, Python programming for big data, and essential tools like Kafka, PyFlink, Elasticsearch, Kibana, and Pydoop (HDFS).
From data ingestion to transformation, real-time processing to storage, this course covers it all, empowering you to build scalable and efficient streaming pipelines.
What sets this course apart is its practical focus.
You'll dive into actual implementation, learning how to consume data from Kafka topics, process it using Python, and store it in Hadoop Distributed File System (HDFS) using Pydoop.
Gain invaluable experience in working with real-time data, handling big data challenges, and designing end-to-end streaming pipelines that deliver actionable insights.
Whether you're a seasoned data engineer looking to enhance your skills or a Python developer venturing into the world of big data, this course offers a beginner-friendly approach with step-by-step instructions
This is complete Big Data Streaming hands-on experience where you'll learn to build an end-to-end stream processing pipeline from scratch using Python., we'll build a powerful end-to-end stream processing pipeline using Flink (PyFlink), kafka , Hadoop HDFS, Elasticsearch, and Kibana !
Join us today and embark on a transformative journey to become a proficient builder of end-to-end streaming pipelines using Python Kafka, Flink (PyFlink), HDFS (pydoop) , Kibana and more +
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 streaming pipelines, helping them gain confidence and practical skills in handling real-time data.
Big Data Landscape is a team of Big Data experts passionate about unleashing the full potential of data-driven solutions. Our mission is to make the complex world of Big Data accessible and understandable to individuals and businesses alike.
With a shared enthusiasm for data and technology, our team is dedicated to helping learners and organizations harness the power of Big Data. We believe that data holds the key to unlocking valuable insights, driving innovation, and making informed decisions that can transform businesses.
As experts in the field, we have accumulated years of hands-on experience working with diverse datasets and mastering a wide array of Big Data technologies. From Hadoop and Spark to Flink, Airflow, Hbase, Hive, Kafka, and more, we have navigated the intricacies of these tools, gaining invaluable expertise along the way.
At Big Data Landscape, we have carefully designed our courses and content to cater to various skill levels, from beginners to experienced professionals. Whether you are just starting your journey into the world of Big Data or seeking to expand your knowledge, we offer comprehensive yet approachable learning experiences.
Our passion for a hands-on approach ensures that our courses are filled with engaging exercises and real-world examples, allowing you to bridge the gap between theory and practice seamlessly. You can expect step-by-step guidance, empowering you to build end-to-end streaming pipelines and tackle real-world Big Data challenges confidently.