The final project grading system is bad. Even you follow all the steps accordingly, you might not be able to find the same coefficients as required.

The updated course is well organized and useful for a workflow or a standard procedure of PySpark.

Great blend of course content for starting a career in machine learning with Spark.

Excellent learning experience - well-designed content and practical sessions.

This course gives good overview about ML with Spark.

Simple, understandable, and learnable :)

The course is hands on and very relevant

Very good introduction to Spark ML

the lab are very helpful

Great Course

Great!

good

/

Spark is build to work with distributed systems. But here it looks like it is some strange twin of pandas. Some basics of Distributed Systems wanted with at least one at least theoretical examlple.

Pretty good. I know feel moderately confident in using the spark shell. I'd have liked some more details about precisely how the partitioning of work for ML functions worked. I was a bit annoyed that the final project was more or less identical to the final project, which was a bit tedious. In general the exercises were kind of tedious are formulaic, but by the end it started being a bit fun because you came to remember all the times. It was good that this gave you hands on experience with pyspark.

The course is too much focused on Apache. I would have appreciated more ML theory and practical examples.