The Typesafe Scala 101 for Data Science Curricula is designed to give experienced Data Developers and Data Science the knowhow to confidently start programming in Scala for data science tasks. The course ensures they will have a solid understanding of the fundamentals of the language, the tooling and the development process as well as a good appreciation of the more advanced features. If students already have Scala programming experience, then this course could be a useful refresher, yet no previous knowledge of Scala is assumed.

The “Spark Overview for Scala Analytics” course will cover the history of Spark and how it came to be, how to build applications with Spark, establish an understanding of RDDs and DataFrames, and other advanced Spark topics. Apache Spark™ is a fast and general engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning and graph processing. Having finished this class, a student would be prepared to leverage the core RDD and DataFrame APIs to perform analytics on datasets. This course is meant to be an overview of Spark and its associated ecosystem. For deeper understanding of Spark, we recommend that students take the Spark Fundamentals courses I and II.

Apache Spark™ is a fast and general engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning and graph processing. This course shows how to use Spark’s machine learning pipelines to fit models and search for optimal hyperparameters using a Spark cluster.