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

4.3

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2,050 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

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

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326 - 350 of 460 Reviews for Fundamentals of Scalable Data Science

By Cosme B M R

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May 1, 2020

The topics are difficult but the course is very good and the teacher is well qualified.

By Mark B

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Apr 17, 2020

Hard to follow at times... was able to get a lot of assistance in discussion forums

By shubham b

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Jan 5, 2021

Nice introduction to the differences between "normal and scaleable" data science

By bahadır y

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Aug 16, 2019

At first, I'm not sure what to do and it is hard for me to set up environment.

By deepshikhar

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Sep 26, 2018

The last quiz needs to be reviewed, otherwise awesome start to specialization

By Eugene N

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May 12, 2020

I actually loved this course because it helped augment my spark basic skills

By Revalino J C S

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Jan 4, 2019

The environment setup is a little cumbersome due to constant changes in UI.

By Kaiqi Z

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Apr 5, 2020

The assignment is a little bit simple, but the knowledge is quite helpful!

By Suyash

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Sep 23, 2019

There are a lot of glitch with the assignments, hope it gets fixed soon

By Pablo R L

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May 22, 2020

Too advanced material for introductory course. Excellent exercises.

By Matthijs K

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Feb 6, 2019

Sets you up well for working with Spark within the IBM Environment.

By Vinita S

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Sep 20, 2020

Harder assignments would been nice and maybe a little more reading

By Tushar J

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Jul 14, 2020

Good course. The pace was good and the material was enough for me.

By Zheng Y

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Apr 10, 2020

Assignments are too simple -- too similar to the course material.

By Harsh

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Feb 3, 2019

Quite Good. But sometimes i had trouble following instructions.

By Raj N

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May 13, 2017

Great introduction to Data Science, IoT and scalable computing!

By Abhay B K M

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Jul 3, 2020

It is hard to follow as it is very advanced and unevenly paced

By Daniel H

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Dec 20, 2020

Short and to the point lessons.

Exercises somewhat too easy.

By ANUBHAV M

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Apr 27, 2020

More interaction with the instructor would be appreciated.

By Dmytro T

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Jun 18, 2019

Cool as for first benchmark. But a bit a lot of IBM tools)

By Mahyar H

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Sep 20, 2022

Assignments should be a little bit more challenging!

By Jon H

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Feb 9, 2019

Good course, instructor was extremely knowledgeable.

By Hunter P

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May 11, 2021

Great course! Could delve deeper into more topics.

By Syed Q R Z

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Apr 15, 2022

The content was good although needs to be updated

By JunYeol L

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Jun 26, 2020

It's really good and easy to learn about pyspark.