February 2022
Beginner to intermediate
4h 35m
English
on-demand course
Real-Time Stream Processing Using Apache Spark 3 for Python Developers
with ScholarNest
Closed Captioning available in English
Overview
In this 4 hr course, you will learn how to build real-time stream processing applications using Apache Spark. Through hands-on examples and live coding sessions, explore concepts like Spark structured streaming APIs, Kafka integration, and much more to start creating your own applications.
What I will be able to do after this course
- Understand how to implement stream processing using Apache Spark.
- Master concepts such as state-less and state-full streaming transformations.
- Learn to work with Kafka and integrate it with Spark.
- Explore advanced topics like watermarking and memory management for streaming joins.
- Be capable of building advanced real-time stream processing solutions with confidence.
Course Instructor(s)
The course instructor is a seasoned data engineer with extensive experience in stream processing and big data technologies. With a passion for applied learning, they teach by example, ensuring students can directly apply the concepts covered. Their approachable teaching style supports learners of all backgrounds.
Who is it for?
Ideal for software developers and architects aiming to design and build big data engineering projects with Apache Spark. Learners should have foundational knowledge of Spark, experience with Spark Dataframe APIs, an understanding of Kafka basics, and familiarity with Python programming. This course will empower them to grow their data engineering expertise.
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