good

nice

good

good

good

cool

Gud

...

no

V

G

G

El curso fue muy util e interesante, y mucho de lo aprendido sirve para aplicarlo en el mundo laboral de la sociedad actual. Me gustaron los módulos que tenía y los distintos retos que proponía. Sin embargo, se nota que el curso no está actualizado en términos de las herramientas que pide utilizar lo que frena mucho la fluidez del aprendizaje. Por otro lado, se nota que los mentores y profesores no están pendientes del curso. En el foro hay preguntas que se repiten y se repiten y no hay respuesta por ningún lado de nadie distintas a otros estudiantes que, o tienen las mismas dudas, o que lograron de alguna forma resolver la duda. Pienso que al ser denominado como curso, alguien debe estar pendiente de las dudas que puedan surgir.

I especially enjoyed the hand-on exercise of week 6 and all-in-all the lectures. They give a good overview on various data integration tools.

Though, I think the virtual machine and some documentation around it needs an update. If you do not finish exercises in one sweep, it is often not obvious how to restore the original settings. I think I've spent almost the same time trying to get the environment on my virtual machine running as with the actual doing in the exercise. I know that this might even reflect the life of a data scientist but some checker scripts which test, if hadoop is running properly, environment variables are set correct, the right version of java is in the path, and so on would be really helpful.

Serious problems with the hands-on assignments. I consider myself a fairly seasoned programmer, with quite a few years of Python under my belt. I still spent many hours on the final project, searching around CentOS forums for ways to troubleshoot Pyspark (the last assignment takes place in a virtual machine). I would recommend not taking this class until you have a very solid understanding of Python and, be aware, this requires bravery in the face of the command line. Not for the faint of heart. I learned A LOT about MongoDB, Linux, PySpark, Hadoop, and conceptual big data as a whole.

The course content is very well thought out and presented.

Hands-on exercises remain a challenge as many things don't work. It takes the mindset of problem-solving (not just in big data, but also in debugging, figuring out how to get different scripts to run, how to set environment variables etc.) to be able to complete all exercises in this course. I suspect that many people might get discouraged and quit the course midway.

The final week's exercises did test my programming skills to a very large extent but gave me a good understanding of the course concepts.

A very good course overall.

Overall very solid course, for the last week, I really enjoyed the fact that it was hands on and made you think and challenge yourself.

For the final project, the data was difficult to process. I was able to do all the major steps, but some minor issues made the task needlessly difficult. Still, I think these kinds of hands on experiences are very important since processing data IRL is not easy and you run into tons of issues.

Amazing course to learn the fundamentals and get hands on experience with mongoDB and pySpark. Course is a little bit challenging due to some errors in guidelines for setting up some working environment and with solutions to final quiz. Would have given 5 stars if those issues discussed on the forums would have been answered. Overall, great learning experience.

The course was interesting and challenging. I definitely learned a lot. As a beginner, my programming skills are limited. Thus, I would have liked a little more guidance for some practical aspects of the final exercises. It would have saved me some time. However, I recognize the added benefit of being obliged to find by myself.

I had a considerable difficulty with the last exercise because it seams to aim to a different level of students than the ones that followed the rest of the course. I would suggest to put the rest of the course, videos, exercises, etc. to the level of the fine_project which, in my opinion, is the correct level.

The theoretical material is perfectly laid out. Hands-on sessions were a bit disappointing. The recommended version of Splunk software has long been unsupported, and newer ones have failed to install. In some places, the explanations are very vague (for example, how to export data.

The course exceeded my expectations in many regards — especially in the depth of information supplied and the access to the instructor for feedback on work in progress. In a very non-threatening environment, I learned key principles of design that I can implement immediately.

There's the need for more examples, even some errors, so we can learn the importance of some syntax errors and how to know or to solve them.

Overall information is good and the examples/questionnaires but maybe more syllabus or links to info that helps improve what it's learned.

I felt this module, like most, represented good value for money. It's obviously not exhaustive, but you shouldn't expect it to be for the price.

The final quiz was a nice challenge and struck a good balance between course material and requiring you to research information online.

This is a very descent to understand MongoDB and Apache Spark. It contains hands on assignments will will allow you to learn how to handle these two software. The course is introductory level, and I recommend this course to people who have not used MongoDB and Apache Spark.