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Course
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Streaming Data Processing with Python
Real-time data processing is essential for modern applications. This course will teach you how to stream, process, and analyze real-time data using Kafka, Faust, and PySpark Streaming with Python.
What you'll learn
In today’s data-driven world, processing and analyzing streaming data in real time is crucial for applications in finance, IoT, fraud detection, and more.
In this course, Streaming Data Processing with Python, you’ll gain the ability to build real-time data pipelines using Python and popular streaming frameworks.
First, you’ll explore the fundamentals of streaming vs. batch data processing, understanding latency, throughput, and state management. Next, you’ll discover how to stream data using Apache Kafka with Python, including producing, consuming, and managing Kafka topics efficiently. Then, you’ll learn how to implement real-time stream processing using Faust, a Python-based alternative to Kafka Streams. Finally, you’ll learn how to scale real-time processing using PySpark Streaming, handling large-scale streaming data efficiently. When you’re finished with this course, you’ll have the skills and knowledge needed to build real-time data pipelines using Python for streaming applications.
Table of contents
About the author
Harsh is a software engineer with 4+ years in Data Engineering, Data Science, and Gen AI, skilled in big data, cloud platforms, and data frameworks. He’s also passionate about travel.
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