Chevron Left
Back to Fundamentals of Scalable Data Science

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

1,980 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


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.


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

Filter by:

326 - 350 of 447 Reviews for Fundamentals of Scalable Data Science

By Pablo R L

May 22, 2020

By Matthijs K

Feb 6, 2019

By Vinita S

Sep 20, 2020

By Tushar J

Jul 14, 2020

By Zheng Y

Apr 10, 2020

By Harsh D

Feb 3, 2019

By Raj N

May 13, 2017

By Abhay B K M

Jul 3, 2020

By Daniel H

Dec 20, 2020


Apr 27, 2020

By Dmytro T

Jun 18, 2019

By Mahyar H

Sep 20, 2022

By Jon H

Feb 9, 2019

By Hunter P

May 11, 2021

By quais z

Apr 15, 2022

By JunYeol L

Jun 26, 2020

By Atif A G

Jun 10, 2020

By Tinguaro B

Oct 4, 2018

By Giovani F M

Dec 20, 2019

By Akash S

Jul 4, 2020

By Francesco C

Feb 25, 2021

By Rong L

Jul 18, 2020


Apr 10, 2019

By Heyimeng

Oct 21, 2020

By Caner B B

Nov 19, 2020