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Opiniones y comentarios de aprendices correspondientes a Fundamentals of Scalable Data Science por parte de Habilidades en redes de IBM

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Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models. In this course we teach you the fundamentals of Apache Spark using python and pyspark. We'll introduce Apache Spark in the first two weeks and learn how to apply it to compute basic exploratory and data pre-processing tasks in the last two weeks. Through this exercise you'll also be introduced to the most fundamental statistical measures and data visualization technologies. This gives you enough knowledge to take over the role of a data engineer in any modern environment. But it gives you also the basis for advancing your career towards data science. Please have a look at the full specialization curriculum: If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link After completing this course, you will be able to: • Describe how basic statistical measures, are used to reveal patterns within the data • Recognize data characteristics, patterns, trends, deviations or inconsistencies, and potential outliers. • Identify useful techniques for working with big data such as dimension reduction and feature selection methods • Use advanced tools and charting libraries to: o improve efficiency of analysis of big-data with partitioning and parallel analysis o Visualize the data in an number of 2D and 3D formats (Box Plot, Run Chart, Scatter Plot, Pareto Chart, and Multidimensional Scaling) For successful completion of the course, the following prerequisites are recommended: • Basic programming skills in python • Basic math • Basic SQL (you can get it easily from if needed) In order to complete this course, the following technologies will be used: (These technologies are introduced in the course as necessary so no previous knowledge is required.) • Jupyter notebooks (brought to you by IBM Watson Studio for free) • ApacheSpark (brought to you by IBM Watson Studio for free) • Python We've been reported that some of the material in this course is too advanced. So in case you feel the same, please have a look at the following materials first before starting this course, we've been reported that this really helps. Of course, you can give this course a try first and then in case you need, take the following courses / materials. It's free... This course takes four weeks, 4-6h per week...

Principales reseñas


13 de ene. de 2021

The contents of this course are really practical and to the point. The examples and notebooks are also up to date and are very useful. i really recommend this course if you want to start with Spark.


21 de jul. de 2021

Nice course. Learned the basics of a lot of different topics. Nice to do a large Data Science project in the last part. So you can apply all learned theory

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351 - 375 de 450 revisiones para Fundamentals of Scalable Data Science

por Heyimeng

21 de oct. de 2020

i think it is a bit too simple

por Caner B B

19 de nov. de 2020

please include more practice

por Michal P

28 de mar. de 2019

Very nice introduction

por Elias L

31 de dic. de 2018

Have been a good one!

por jin p

4 de jun. de 2019

Thanks, really helps

por Deleted A

11 de feb. de 2019

Can I get a badge?

por Bladimir P

24 de sep. de 2020

Great course!

por Ahmed T

10 de mar. de 2019

Excellent :)

por Andrey O

10 de ago. de 2018

Good course!

por Marvin L

2 de abr. de 2020

it was good

por Fernando P

2 de oct. de 2020

Very good!

por Caroline L

27 de abr. de 2021

Too easy.

por Italo L

29 de feb. de 2020


por Carlos F

29 de abr. de 2021

This was not especially well made. A number of the examples shown on videos don't necessarily work or are outdated with respect to the platform or the datasets you're working with. Perhaps, greater attention should be given towards guiding the student to the github repo were the notebooks are up to date and working properly. Otherwise a good course, definitely not introductory to cloud, if that's what you're looking for. There is some high level programming that I'm defnitely not prepared for but the notebooks are so complete that I did not have to apply myself so much. So on the one side I appreciate the ease of the notebooks but, on the other side, have some doubt as to the practical knowledge acquired. Hoping later courses in the specialization clear this out for me.

por Nikhil P P

8 de feb. de 2019

It was difficult to follow the IBM cloud setup since it was constantly changing, I couldn't understand the reason for using python2.7 since its only 10 months before it wont be supported by the community. Sometime instructors' pronunciations were not clear and and thus added extra confusion. However, instructor do actively participate in helping with discussions. Audio and video quality were also not very good. This course is a very basic introduction to IBM cloud and general stats. Prior knowledge of spark is useful. Overall the course is nice introduction to IBM cloud if one is interested.

por Jennifer K

11 de mar. de 2021

This is a good introduction and overview to working with Spark. The assignments are very straightforward and I think that the biggest benefit is learning how to set up a work-station in IBM and working with your notebooks there. One thing that I think should be improved is the version of Python and Spark that is being demonstrated: the lectures should update to Python 3 and we also have Spark 3 by now; focus should be on data frames instead of RDD. Also, lots of links need to be updated because their references are deprecated and so no longer exist.

por Bayram

25 de feb. de 2020

This is a very basic course even if it's my first interaction with Apache Spark. For sure, it gives some information. But I found the timeframes stated too long. You feel like you'll get a lot of information. But a week of videos and readings and assignments can be done in 1.5-4 hours depending on your experience how much time you spend on assignments.

Also, there are many materials that are outdated. That should be fixed if this course carries the name of IBM.

por Rameez R

1 de sep. de 2020

The coding part is easy to comprehend but the course does not offer much opportunity to practice and learn the coding. The assignments are straight forward and doable. Sometimes it is hard to read the code in the videos even at 720p as it appears blurred. The subtitles cover some of the formulae shown at the bottom of the video and there are many mistakes in subtitles.

Overall, it is a good introductory course that gives you an idea of about Apache Spark.

por Joseph B J

27 de abr. de 2020


The Course touches the important topics related to scalable data. The quizzes & assignments were challenging and the fun to solve.


Though the course touches the important topics, it does not go deep into it. Some of the codes provided in the video didn't work with the current version of python and spark. For example the code for finding the median. The Cognitive IOT app development method provided was broken and it wasn't the right way to do it.

por Eleni K

10 de oct. de 2019

I was really looking forward to this specialization but from the very first course I am really disappointed. The videos refer to various not updated information and then suddenly we are expected to do an assignment that was not at all explained in the course. I am not saying it is difficult, or not achievable but to be honest until now (week 2) it feels mostly like a waste of time.. Really sorry for this review.

por Moises D P A

2 de jul. de 2020

The course should be updated. It's hard work, but it's worthy. I'm sure students get confused a lot with the inconsistencies generated by the update of IBM Watson. So, there is some minus difference nowadays with what's being taught. Anyways, I think the content of the course is perfect to start. I learned satisfactory tools and ideas about how to handle big data.

por Dr. J A V

17 de ene. de 2019

The idea and material behind the course is really interesting, albeit very basic. Some of the exercises and quizes, like the ones of interpreting plots are not very clear, since the plot quality is low. However, this is a very nice introduction to ML and IoT using Watson. Looking Forward for the next courses of the IBM Degree for advance data science

por Cedi K

29 de ago. de 2021

In my opinion, the slides for this course should include more graphics. Especially showing the relations between different tools and objects. As an example, the Video "Introduction to Cloudant" would profit a lot if some graphics showing the relations between it and Apache Spark would have been used instead of simply going over bullet points.

por Carolin W

6 de may. de 2022

- The provided Code and ressources are sometimes quite outdated. This lead's to Website Links, that are not up-to-date anymore, and errors within the programming environment when running the Code.

- The assignments are sometimes way to easy to solve, where a copy and paste of exercises is sufficient to successfully submit a "3 hour" Assignment

por Dmitry S

10 de mar. de 2020

The course is called 'Fundamentals' and is indeed pretty basic. A good quick overview of the most basic concepts. Sometimes too basic to qualify for an Advanced course on Coursera. So, not really clear for which audience the course is.

Another fundamental course that does a better job is Spark Fundamentals from