I recently completed the course “Taming Big Data with Apache Spark and Python – Hands On!” on Udemy, taught by Frank Kane. I wanted to share my thoughts on the course and provide my opinions on what I enjoyed and what I didn’t like as much.
My thoughts
If you are already familiar with Spark and Python and want to delve deeper into the subject, I believe this course provides a solid foundation. It begins with a comprehensive introduction to Spark, including a thorough exploration of its internals and architecture. I found these materials to be particularly helpful and well-explained.
While the course does contain some outdated material, I personally did not mind spending time learning about RDDs, as it helped me to understand their differences to dataframes. However, I do understand that some reviewers have found this aspect of the course to be a drawback. Overall, I found the examples to be fairly basic, but effective for learning about the various capabilities of Spark. I would recommend actively typing out the code as you follow along, as this can help you to better understand the logic. Personally, I would have preferred if Frank had typed out the code as he explained it, rather than simply demonstrating it, so students could follow along with this thought process more closely.
I found the sections on machine learning and streaming to be somewhat rushed, with a reliance on the assumption that the code would work as expected. While this may not be ideal, it is worth noting that there are entire courses out there dedicated to these subjects, so it is not necessarily unexpected to receive only a broad overview in this course. That being said, the course does provide a good introduction to machine learning and streaming, and can serve as a starting point for those interested in delving deeper into these topics.
So..
Overall, I would rate this course as 3 out of 5 stars for my personal experience. While there were some aspects that I found lacking, I will definitely consider taking additional courses from Frank Kane in the future.
