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

4.3
stars
2,046 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: 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 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... https://cognitiveclass.ai/learn/spark https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/f8982db1-5e55-46d6-a272-fd11b670be38/view?access_token=533a1925cd1c4c362aabe7b3336b3eae2a99e0dc923ec0775d891c31c5bbbc68 This course takes four weeks, 4-6h per week...

Top reviews

ZS

Jan 13, 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.

EH

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

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376 - 400 of 459 Reviews for Fundamentals of Scalable Data Science

By Joseph B J

Apr 27, 2020

Good

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

Bad

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.

By Eleni K

Oct 10, 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.

By Moises D P A

Jul 2, 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.

By Dr. J A V

Jan 17, 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

By Cedi K

Aug 29, 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.

By Carolin W

May 6, 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

By Dmitry S

Mar 10, 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 cognitiveclass.ai.

By Alex P

Jul 7, 2020

Very very basic. Far away from advance. I did more than the whole course in just one lecture at my university (LSE). And that lecture at the university did not assume that we already got experience with Spark or python. I still give three stars because it is still quite ok, just far away from advanced.

By Sonja T

Jul 8, 2021

Good material. Hard to understand the instructor's English. No professionally presented. Assignments are too easy, and we didn't get good, meaningful practice. Quizzes often address information that either the instructor failed to present well, if at all, or made mistakes on.

By Tony H

Nov 4, 2019

I felt that, for a course labelled as 'Advanced', there were too many trivial questions in the quizzes and too much hand-holding in the programming assignments. That being said I did enjoy the course and learned quite a lot and look forward to the next one in the specialisation.

By Mohamed A T

Jan 29, 2020

The course was great, the material and the assignments.

IBM Watson platform was easy to use.

But I can't see how this course is included in the "advanced" data science specialization.

Honestly I was expecting a more advanced course. But we'll see with the next ones.

By Csaba O

Sep 9, 2019

The content was OK, but I have expected more. Probably it was too basic for me. I would have been happy to see some more real life examples, like when to use the different statistics to solve real problems, not only the theoretical ones.

By Alex K i d V

Dec 1, 2021

Gives you a great understanding about the fundamentals and how apache spark works. However, some exercises and files are outdated and it will not take you the amount of time the course info indicate, fow me it was less than half of it

By Slim O

Apr 16, 2020

A detailed explanation on the trade off of different approaches that can be used in Big Data but there is not enough examples of manipulating big datasets

By Rama K R

Apr 20, 2020

I believe that the assignments of this course should have been a bit more rigorous. Also, there should have a been a bit more focus on Apache Spark.

By Kaiwalya

Mar 21, 2020

The course content is amazing but the instructor's accent is very difficult to understand and in some videos subtitles in English weren't available.

By Pranav V

Oct 5, 2020

give lot of details about pyspark like basics.

its getting hectic with just the small details given in videos.

videos needs to be changed and updated

By Omphemetse M

Feb 4, 2021

Good introductory course, however it would be better if the assignments were more involved rather than having the code typed out already for us.

By Zhou M

Jul 22, 2021

Some of the content in the video should have been updated due to the change of interface. Had some difficulty setting up the environment.

By Vaishnavi M

Jun 18, 2020

Topics can be taught a bit more slowly, it was a bit difficult for me to understand. Otherwise, the content covered was very helpful!

By Trung H N

Aug 2, 2021

The content was okay, but it is pretty basic. There is legacy from previous versions of the course that needs better transitions

By BAUDRY S

Nov 20, 2019

The functions we need to complete looks quite messy, it'a little bit overwhelming especially for people who start with spark.

By Camilo A S B

Sep 5, 2020

I felt the course is out of date and have worked on these classes to update it so that I can run the video classes again

By Mohamed M

Apr 5, 2020

the assignment is required to be in sparkaql functions however the course is just using spark with built in functions

By Nikhilanj P

Sep 6, 2019

Too many legacy issues. Would be better to start a new course altogether and maintain same syntax,etc.