excelente

Great!

USEFUL

good

good

Nice

good

good

wow

good

Excellent. But would have liked to have more detailed walk through on how to set-up (not just a reading) on my own computer and practice lab on that. Also, too many of the slides were just bullet points and could have been more visualized to ensure architectural themes are easily remembered (e.g. monitoring module was just textual and diagrams could have been more specific - especially linked with Sparks UI more closely than a few images after many bullet vis-a-vis nicely explained job/stage/task hierarchy and how it relates to client mode set-up.)

Es un gran curso en donde he podido afianzar conceptos fundamentales tanto en Hadoop como en Spark. De no ser por estar absolutamente atado y dependiente de la plataforma en la nube de IBM, sería un curso perfecto. Me gustaría que en la primera parte del curso enseñaran cómo montar una plataforma localhost y luego pasar a conocer las ventajas de montar todo rápidamente en la muy buena plataforma de IBM.

+ great IDE for hands-on labs + good intelligibility of computer-generated voice reading the texts - slightly boring data sets - some factual errors in the quizzes (e.g. radiobuttons instead of checkboxes for questions with multiple correct answers)

I like the content about Spark, it was well organised and demonstrated with hands-on lab, but not for Hadoop (HDFS, Hbase etc). plus the long videos with robotic voice makes it hard to concentrate. In general it was a good course

Synth voice narration quality is truly annoying. I'd expect better from IBM. Course materials are quite superficial, which I guess is acceptable for an introductory course.

This is really helpful for me to understand Big Data and Apache Spark!

hands on lab and quizzes at the end of each session was very helpful

It's very good introduction with hands on lab.

should have more practical knowledge

Good course

GOOD

There are three major concerns I have with this course: 1) Content Depth and Structure: The course content feels overly basic, even for an introductory level. The lab exercises are too simplistic and fail to provide meaningful hands-on experience. There is no technical final assessment; the concluding quiz is entirely theoretical. Questions about IBM products or statistics like "the projected growth of data" seem irrelevant and out of place. 2)Lack of Conceptual Clarity and Practical Application: Key concepts like shuffling, grouping, and filtering are not explained or demonstrated in sufficient depth. Including practical examples to showcase their impact would significantly enhance understanding. The course neglects to explain the execution plan in Spark, particularly how it operates and its implications for application performance. This is a critical topic that deserves proper attention. The explanation of differences between RDDs and DataFrames is confusing, even for someone with basic knowledge. Similarly, the coverage of Spark SQL and functions lacks clarity and structure. A more straightforward approach—e.g., showing three ways to accomplish a task, comparing them, and contextualizing their usage in real-world scenarios—would be far more effective. The inclusion of Pandas is unexpected. While it’s noted that Spark RDDs/DataFrames can be created from Pandas DataFrames, there was too much emphasis on it, and in the same stage of course foundational functions like read.csv are not even mentioned. This omission contributes to a sense of disorganization and a lack of a coherent teaching strategy. 3)Presentation and Delivery: The video materials are AI-generated, and this detracts from the learning experience. Personally, I found the videos too short, with unnecessary and repetitive intro/outro segments that quickly became irritating. This format undermines engagement and suggests a lack of thoughtful design. A human instructor narrating the content could provide a more engaging and dynamic learning experience. A human presenter might also recognize and address the lack of substance in the explanations, resulting in clearer and more effective teaching. Overall, the course feels like a collection of loosely connected topics rather than a carefully designed curriculum. A greater focus on depth, practical application, and a more personalized delivery would significantly improve the learning experience.

Good theoretical knowledge on Big data, Hadoop and Apache Spark. However the labs were of very limited scope and didn't provide full hands-on exposure of the tool. Concepts were really difficult to grasp and had to go through the course content few times to clear the final assignment. Not very impressed with the articulation of the concepts discussed in this course. so 3 stars from me.

This is a good course for in depth theoretical knowledge about spark and hadoop but it does not have enough hands-on and the exercises which do have hands-on lack proper explanations of the code that we just mostly copy and paste

The automated voices are really distracting, and the explanations in the course are quite surface level. I enjoyed the hands-on training part of the course though.