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

4.3
797 ratings
163 reviews

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: https://www.coursera.org/specializations/advanced-data-science-ibm 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 ibm.biz/badging. 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 https://www.coursera.org/learn/sql-data-science 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 This course takes four weeks, 4-6h per week...

Top reviews

XW

Apr 11, 2017

Very useful courses to take if you are beginner of data science. The course was not detailed enough sometime. But you will surely get a global view of IOT data analysis after this courses.

HS

Sep 10, 2017

A perfect course to pace off with exploration towards sensor-data analytics using Apache Spark and python libraries.\n\nKudos man.

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1 - 25 of 163 Reviews for Fundamentals of Scalable Data Science

By Mike D

Nov 29, 2018

Currently, it is not advisable to take this course.

I have finished the excellent IBM Data Science Professional Certificate series on Coursera and wanted to improve my knowledge of scalable Data Science with this series. Unfortunately, the videos and advice are extensively outdated. Python 2 is used through this course and the instructions of how to set up Node-RED and Cloudant do not work. I have been trying to work myself around that but then again, I wouldn't need this course in the first place and it only leads to confusion. Also, instead of the Cloudant application UI, Kibana seems to be used now, which there is no introduction to. I have noticed that Romeo Kienzler, the course lead, is very active and dedicated in the discussion forums. I am afraid, I have to give this course 0 stars for content (for now) and 5 stars for course lead dedication.

By David-Leigh B

Dec 18, 2018

IBM cloud environment is buggy and inconsistent with lectures.

When deploying services it sometimes fails and you are unable to remove them, rendering the account inoperable (as you have limits on free tier)

By Vincenzo M

Apr 13, 2018

I'm really disapointed with the "Fundamentals of Scalable Data Science" course from IBM. The videos are referring to an outdated software releases, with really different screenshots from the ones existing on IBM platform. The discussions refers to code samples different from the ones available for download (flow2.js) and to applications present on the IBM Bluemix platform, without explaining where to found or how to create them. All these discrepancies make really difficult to follow the course. LBNL, the speaker is one of the most boring ever encountered in a webinar, barely able to read in english language. Being a course organized by IBM for such an important topic as Watson, I expected a much higher level of quality. I hope that the IBM staff will be able to perform a deep review of this series of course.

By Ryan S

Dec 23, 2018

Good:

Introduces Scalable Data Science and setting up the proper environments.

Areas for Improvement:

Not fully compatible with Python 3.5 (frustrating)

Could use some pre-requisite course material such as basic SQL and walk-through of pyspark SQL DataFrames.

Structure and presentation could be improved and reorganized.

Instructions need proof-reading.

By Marcin S

Apr 14, 2019

not enough additional materials

By Denys v K

Dec 27, 2018

Very steep learning curve! Getting everything set up correctly is not very user friendly at this stage. Once everything is setup the material presented is very interesting. However, I prefer the tests (assignments) to actually test what was being taught and not something quite distinct (teach python; test spark SQL). The many comments in the forum attest to the issues for this course. Good start but needs improvement. Thank you.

By Robert M

Jun 12, 2019

Training Videos are pretty good for a beginner but to consider this an advanced course is incorrect. Intermediate at most. In addition the application of lessons to assignments were minimal as the answers needed for the assignment were not related to the content that was discussed, just very simple fill in the blank.

By Vuong B A

Nov 30, 2018

Setup process is tedious

By Dr S K

Jan 18, 2019

The concepts taught in this course are very current. I would appreciate some more in depth practical/technical information about IoT, also about apache spark and the overall mechanism of action in the real world. The assignments I did not enjoy much, I found them rather uninteresting, although I appreciate the concept behind them and I can see why they were chosen. I really appreciate Romeo - I find him very interesting and I can tell he has a lot of experience and passion for what he has been doing. This particular course could provide a lot more information and education on scalable data science. Overall I found it ok, but I do appreciate that this is a new subject area and people have trouble collating material together. If Romeo would team up with people who have experience in teaching I think this course would have been outstanding. In any case I really appreciated his very hard work and I am very grateful.

By Marius J

Jul 06, 2018

This course does cover the needed fundamentals but needs a serious audit and edit of content, transcription, testing and grading for accuracy, conflicting instruction, and actual relevant instructional feedback.

By Marco D

Aug 17, 2019

Assignments are too easy. The English pronunciation of the teacher is quite bad, sometimes I cannot understand and the subtitles are often wrong. I would be interested in an explanation that helps to setup spark in the local computer, instead of using IBM products.

By Gabor K

Nov 10, 2018

I will un-enroll after 7 days in the course as the basic cloud environment setup did not work as written in the course handouts and videos. Which could be okay, however noone replied to my questions for 4 days on that, and the reply tips did not work either. Updating with screenshots, explanations no answer till today so what would have been a 15 minute job takes 7+ days here. At other coursera and competition platforms all my questions got answered in hours vs weeks as in this course.

By Qian L

Jul 06, 2019

If there was negative score, I wouldn't even hesitate to give that to this course. I understand coursera is actually trying to do good to the society and change the way education works in the past. But bad UI won't get you any further. About this course, I don't know why this Romeo guy is allowed to teach here. Extremely unusable tutorials, extremely bad organization of the the materials, extremely bad accent, extremely unusable IBM cloud service, extremely outdated tutorial for environment setup, and you name it. This guy can't even articulate himself. Please stop doing this to the user since now coursera started charging subscription fees. If there is even no quality control and this kinda of bad actor is allowed here, what is the difference between coursera and traditional college? Just go to the forum and discussion session of this course and look at the complaints over there. You don't even need to search for complaints since they are there on the surface. Shame on you.

By Mohanad Q A A

Mar 10, 2019

Fuzzy, outdated, low quality course, according to the instructor; he is very busy "TRAVELLING" so that he cannot improve the quality of this course.

My problem is that the programming assignment of week 2 has no meaningful doc-string inside the functions that require coding, I do not know how I can deduce that my implementation is right before submitting to the auto grader.

By Zhihao Z

Jan 04, 2019

I couldn't find most relevant IBM web pages only with the instructions; I spotted typos and bugs in exercises; the most disappointing part is the autograder which malfunctions OFTEN on unclear grounds, I had to submit my assignment multiple times and to test the autograder.

I could have spent less time learning more.

By Jose L R

Sep 30, 2018

Great way to understand and learn open source tools and latest IBM data science offerings.

By Harshit S

Sep 10, 2017

A perfect course to pace off with exploration towards sensor-data analytics using Apache Spark and python libraries.

Kudos man.

By Chirag S

Jul 09, 2018

A Great Course to get an understanding regarding some basics concepts of data analytics through implementation

By Matthew T

Feb 08, 2019

Good course content, however, some of the material especially the IBM cloud environment setup sometimes confusing

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 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 Igor E

Mar 04, 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 Nikhil P P

Feb 08, 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.

By Andrés

Feb 07, 2019

Assigments needs to be better defined and explained