Learn practical Big Data with Apache Spark DataFrames, Datasets, RDDs and Spark SQL, hands-on, in Scala
InstructorDaniel CiocîrlanTechnical modules include specific exercise items following core lecture topics like DataFrames, Datasets, and RDDs to reinforce learning through code.
The curriculum provides clear coverage of the Structured API, including DataFrames and type-safe Datasets for data processing.
Editorial course preview
This view highlights a concrete, legible example from the course presentation.
This course overview slide outlines key learning objectives including DataFrames transformations and Spark SQL, accompanied by a Scala code example demonstrating data reading and writing.
Learner signals suggest the content remains at a more superficial level regarding Spark internals, such as partitioning or debugging data skewness. Note that these signals originated in reviews dated before the most recent update; while the course has a newer update label, it does not prove these specific areas were addressed.
One signal indicates that certain video examples involving date formats may require updates to prevent execution errors. This signal also predates the displayed update label, leaving it uncertain if a correction was made.
The curriculum aligns with the requirement for Scala proficiency and targets those entering the Big Data field.
