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

4.3
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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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351 - 375 of 459 Reviews for Fundamentals of Scalable Data Science

By Atif A G

Jun 10, 2020

Good Course but could have had a lot more detail.

By Tinguaro B

Oct 4, 2018

Great introduction to Data Science on IBM Cloud.

By Giovani F M

Dec 20, 2019

Great course to learn basic knowledge in spark!

By Akash S

Jul 4, 2020

Good course, but assignments are a bit easy

By Francesco C

Feb 25, 2021

Good explanation. Perfect starting course.

By Rong L

Jul 18, 2020

The instructor can be a bit slower.

By ndahimana s

Apr 10, 2019

Nice course with good tutorials

By Heyimeng

Oct 21, 2020

i think it is a bit too simple

By Caner B B

Nov 19, 2020

please include more practice

By Michal P

Mar 28, 2019

Very nice introduction

By Elias L

Dec 31, 2018

Have been a good one!

By jin p

Jun 4, 2019

Thanks, really helps

By Deleted A

Feb 11, 2019

Can I get a badge?

By Bladimir P

Sep 24, 2020

Great course!

By Ahmed T

Mar 10, 2019

Excellent :)

By Andrei O

Aug 10, 2018

Good course!

By Marvin L

Apr 2, 2020

it was good

By Fernando P

Oct 2, 2020

Very good!

By Caroline L

Apr 27, 2021

Too easy.

By Italo L

Feb 29, 2020

Great

By Carlos F

Apr 29, 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.

By Nikhil P P

Feb 8, 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 Jennifer K

Mar 11, 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.

By Bayram

Feb 25, 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.

By Rameez R

Sep 1, 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.