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Learner Reviews & Feedback for Fundamentals of Scalable Data Science by IBM Skills Network

2,010 ratings

About the Course

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...

Top reviews


Jul 21, 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


Jun 19, 2021

Great Course but this would have been even a better course if more concepts and details were covered in it. Anyways, still a great course for beginners

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26 - 50 of 450 Reviews for Fundamentals of Scalable Data Science

By Dmitry B

Jan 11, 2019

This course is teaching how to work with data in a distributed environment. While getting used to IBM Cloud takes time, it is definitely a friendlier environment for data scientists and it removes the burden of setting up the infrastructure.

By Igor E

Mar 4, 2019

Good course, but some of the later videos and assignments refer to data generation on Cloudant and NodeRed that made the videos confusing since the Cloudant videos were removed. This caused me to jump between the course and youtube videos to learn about data generation, only to find out it wasn't necessary.

By Miguel A B G

Nov 12, 2018

Eeverything related with the graded assesment in this course fails, it's outdated and the practicla exercises are not well explain, if you are looking for a hard struggle to get very simple things done, this is your course

By Ramkumar K

Apr 6, 2018

Not so worth learning compare to the predecessor of this course. Should have included more assignment would have made the course very interesting.

By Vy D

Jan 25, 2019

Not enough coding, or I would like more interactive coding if that was possible in coursera. Or how would we do this like locally?

By Nicole Z K

Jan 13, 2020

Outdated content, with corrections as annotations in the videos. Not very engaging and has just a little of spark content.

By Ahmed E A T E

Apr 10, 2019

the content is really good but I don't understand the Indian accent well although this guy really did his best

By Mario R

Jul 14, 2019

Need more exercises related to wrangling data and manipulating SQL's with apache spark

By Shubham K G

Jul 4, 2019

Nice but details are not discussed properly only taking names wasnt enough

By Andrés

Feb 7, 2019

Assigments needs to be better defined and explained

By Karthik D

Jan 19, 2019

Too many issues with lab material

By Ozge Y

Jun 23, 2019

I find it unacceptable that the grader still had the same old problems from months ago. Adding notes directly to the python notebooks is not that difficult. #Return 4 significant digits, etc.

Plus, the grader output is not always useful. I execute the function in the python notebook, for whatever reason it does not fail, it works. The grader is more sensitive as it should be but it would be more meaningful at least it mentioned which line it has failed or which cell or which function.

The quizes during the videos seems a bit too random. I expect, if you are interrupting a video, you would be asking a question whose answer would be relevant for the later part of the video. Those pop-ups feels like unannounced midterm exams. There is already a full quiz section for this.

Perhaps my expectations were too high for this course.

By Roger S P M

Jan 23, 2019

Course content contains too much screen capture of clicking rapidly through IBM could menus. In most cases, the version of IBM Cloud now being deployed varies from the course, so students have to figure it out themselves.

Also, explanation of the tools and resources is very short - line one sentence. We are left to figure out what the tools are - cloudant and node-RED especially.

This course and certificate look like they should come after the first Data Science Certificate (9 courses). But there is a definite gap between the two. It is not clear what course is supposed to bridge that gap.

By Dan B

Feb 6, 2019

This course needs work. There needs to be more of a challenge, being an advanced course I expect a certain level of difficulty. I think the knowledge is too high level. There also needs to be more of a hands on approach. Let me connect to the Cloudent service, and more practice using spark and map functions.


Jul 10, 2019

Simply not on the same level as other ML Courses on Coursera. Programming assignments don't require you to do much by yourself. The bits you have to write, you have to guess from function names (no task description or anything is given).

By Suyash D

Aug 13, 2018

Very good course but codes and instructions are outdated. It needs serious improvement on that part. It is costing a lot more time to finish this simple course.

By Sheen D

Sep 1, 2019

Cannot understand what the instructor is saying half of the time... because he speaks really really fast...

By Thanh N N

Jun 20, 2019

The instruction is not so clear. Many mistake launch and grader does not run to score your submission.

By Dorzhi D

Jan 27, 2019

Very fiddly. Video instructions do not correspond to IBM interfaces.

By Martí S C

Dec 8, 2020

I don't understand why the level was marked as advance

By Mateusz K

Dec 23, 2018

Quite outdated and chaotic

By Daya_Jin

Sep 27, 2018


By Sudesh A

Sep 22, 2018

While the course info describes this course as a beginner level, I would not describe it so. A lot of technical terms are thrown around without even saying a word about them let alone explain them.

The course is very disorganized, and the instructions for the assignments are not correct (and outdated). You have to basically figure out on your own how to set up the system before you even start doing the actual assignments. What you actually experience is completely different from what you see in the screenshots of the instructions.

This has been my experience just after being 2 weeks into the course. Hopefully things get better in the last two weeks. Honestly, so far I have only learnt a bunch of names.

I will update my review at the end of the course, if needed.

UPDATE: I eventually decided to unenroll from this course. This course is not worth it, in my opinion.

By Arman I

Apr 1, 2021

The lectures are quite useless. Assignments are almost irrelevant to Apache Spark. Estimated time for the course/assignments are so incorrect. You basically need 10mins instead of 3h to finish an assignment because there's only a couple of lines to fill in with your code.

By biern s

Sep 13, 2020

This is by far the worst.

The content is very poor so that 'advanced' should be removed.

In addition, the lecturer's English is unclear and not easy to understand, however, as there is empty content you don't need to worry.

I just wasted my money and time.