This course is ideal for software developers, data engineers, and big data professionals who want to build scalable data processing solutions using Apache Spark and Scala.
Apache spark and Scala Training
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You will gain a strong understanding of Spark’s architecture and learn how to write efficient Scala-based Spark applications for batch and real-time data processing.
Yes. The training includes practical exercises and real-world scenarios that allow you to implement Spark programs, optimize performance, and work with large datasets.
No prior big data framework experience is required. However, a basic understanding of Java or Scala programming is essential.
Absolutely. The course is designed with enterprise use cases in mind, enabling you to apply Spark and Scala skills directly to production-grade data processing projects.
Yes. Upon successful completion, participants will receive a Florence Fennel Certificate of Completion in Apache Spark and Scala.
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This is a professional training program focused on big data processing using Apache Spark, with Scala as the primary programming language. It covers Spark’s core modules and real-world data processing techniques.
The course is suitable for developers, data engineers, and IT professionals who have basic knowledge of Java or Scala and want to work with large-scale data processing systems.
Participants should have a basic understanding of Java or Scala programming. Prior experience with big data tools is helpful but not mandatory.
The course emphasizes practical learning, including coding exercises, use-case-driven examples, and hands-on implementation of Spark applications.
You will be able to build, optimize, and deploy Spark-based applications using Scala, process large datasets efficiently, and work with Spark SQL, streaming, and machine learning components.
The course duration ranges from 24 to 30 hours, depending on delivery format and customization requirements.
Yes. Learners who successfully complete the program will receive an official Florence Fennel Certificate of Completion.
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