Full Hands on course to become Big Data Engineer: Spark/Kafka/Hadoop/Flume/Hive/Sqoop/MongoDB. Data Engineering course.
InstructorNavdeep KaurEditorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
The course interface displays positive student feedback alongside a structured curriculum covering big data tools including Sqoop, Apache Flume, Hive, and Spark.
This slide outlines the data engineering curriculum roadmap, displaying a timeline that progresses from the Big Data Ecosystem through Hadoop, Sqoop/Flume, Hive, Apache Spark, Apache Kafka, and MongoDB.
Instruction provides depth into Spark internals, covering RDDs, transformations, actions, and cluster execution concepts like shuffle and stages.
The curriculum includes various practical examples using command lines for data engineering tool workflows.
The inclusion of Sqoop may be problematic as it is deprecated and difficult to install in modern environments. One signal from 2023 suggests this difficulty, though the 2025 update label does not prove a correction has been made.
One signal indicates a mismatch between promised Google Cloud instruction and the actual content encountered, alongside reports of insufficient explanation in certain lectures.
While it targets aspiring data engineers, reported mismatches in platform instruction create uncertainty.
