Avis et commentaires pour d'étudiants pour Big Data Integration and Processing par Université de Californie à San Diego

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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.

There were several issues running the hands-on assignments; problems with getting various python tools and/or features. These issues made the labs frustrating at times, take much longer than needed, and quite stressful to complete.

This is an old specialization and must be updated with a variety of necessary modifications done to it in order to keep it running!

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.

Es curso es muy bueno, pero deberían tener más consideraciones o tutoriales respecto a la forma de proceder con los updates de los sistemas. Los aspectos a tener presentes cuando se instalan, los parches requeridos para que ciertos comandos funcionen, etc. Eso resulta muy complejo, en especial por los tiempos de descargas e instalación de los mismos.

Very good course. Not much of programming skills required, only logical thinking.

Good hands on experience but seems the course materials need updating to the current level of versions in the respective tools. Pyspark was an issue right from the start and I have to use other methods to answer the quizzes. I hope I would not be

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.

T​he content of the course is great, well explained. There are some problems with outdated versions of software (python, anaconda and pyspark) that make frustrating completing some exercises and tests. Overall is a very good way to start working with spark, hadoop.

great course, it's quite challenging.

however the setup for quiz was not working for Spark analysis. Reinstalling Spark and associated jar took my time in doing R&D on net to find the solution to run Spark with the mentioned jar files. Overall it's very good course

This is the first course in the big data specialization that has some good hands-on practice exercises. The final project makes you think and explore pyspark features. I would highly recommend it for anyone who wants to get exposure to mongo and pyspark.

Curso notable, completo y didáctico. Sin embargo algunas tareas se hacen muy complicadas para aquellos sin experiencia ni conocimiento amplio en materia de programación, ya que las instrucciones no ayudan por completo para aquellos más inexpertos.

Great course, great presentation!

Just a bit of information overkill with the many tools and techniques that are presented. I would have preferred less tool examples in the hands on, therefore deeper introduction to those that are presented.

Contents are good. The structure of the course is amazing. Must do program to have an insight into the BigData Integration as this will open basic processing techniques and about few of the tools used in BigData a overview of the same.

The virtual machine for running the environment is, at start, a good idea. But even with 8 core i7 with 8G of RAM laptop, it was sometime painful to process the exercices. Maybe an ubuntu/virtualbox/laptop compatibility...

As a beginner course it is pretty interesting. The only drawback is that the assignments in the end require prior programming language knowledge and familiarity with the user interface which the following course lacks.