Course details
Understanding how to manipulate, deploy and leverage Apache Spark is quickly becoming essential for data engineers, architects, and data scientists. So, it's time for you to stay ahead of the crowd by learning Spark with Scala from an industry veteran and nice guy.
This course is designed to give you the core principles needed to understand Apache Spark and build your confidence through hands-on experiences.
In this course, you'll be guided through a wide range of core Apache Spark concepts using Scala source code examples; all of which are designed to give you fundamental, working knowledge. Each section carefully builds upon previous sections, so your learning is reinforced along every step of the way.
All of the source code is conveniently available for download, so you can run and modify for yourself.
Here are just a few of concepts this course will teach you using more than 50 hands-on examples:
- Learn the fundamentals and run examples of Spark's Resilient Distributed Datasets, Actions and Transformations through Scala
- Run Spark on your local cluster and also Amazon EC2
- Troubleshooting tricks when deploying Scala applications to Spark clusters
- Explore Spark SQL with CSV, JSON and mySQL database (JDBC) data sources
- Discover Spark Streaming through numerous examples and build a custom application which streams from Slack
- Hands-on machine learning experiments with Spark MLlib
- Reinforce your understanding through multiple quizzes and lecture recap
Check out the free preview videos below!
As an added bonus, this course will teach you about Scala and the Scala ecosystem such as SBT and SBT plugins to make packaging and deploying to Spark easier and more efficient.
As another added bonus, on top of all the extensive course content, the course offers a private message board so you can ask the instructor questions at anytime during your Spark learning journey.
This course will make you more knowledgeable about Apache Spark. It offers you the chance to build your confidence, productivity and value in your Spark adventures.
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