Learn the latest Big Data technology - Spark and Scala, including Spark 2.0 DataFrames!
InstructorJose PortillaThe curriculum includes specific exercise projects for DataFrames, Linear Regression, Logistic Regression, Clustering, and PCA.
Early instruction is noted for being easily digestible and well-structured for beginners.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This slide highlights that Spark is written in Scala for fast Big Data tasks and outlines learning objectives including Spark 2.0 methods, MLlib library updates, Spark SQL, and DataFrames.
A title slide featuring the official red Scala logo alongside bold black text announcing a full guide to learning Scala programming.
This graphic features a simple laptop icon and clearly labels the section as providing full set-up installation guides for configuring the development environment.
The reliance on Spark 2.0 creates a gap with current Spark 3.x standards, and Databricks interface changes may cause friction.
One sampled review suggests that the transition from introductory Scala to advanced Spark machine learning can feel overwhelming for some learners.
The curriculum aligns with the goal of learning Scala and Spark for those with basic programming knowledge.
