Chevron Left
Back to Fundamentals of Scalable Data Science

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

Filter by:

301 - 325 of 459 Reviews for Fundamentals of Scalable Data Science

By Lucas M B

Dec 2, 2019

Seria ótimo se atualizassem o conteúdo do vídeo para reproduzir a versão atual do sistema e do Python, porém em teoria o conteúdo não deixou a desejar.

By Parth G

Oct 4, 2020

A bit on the easy side especially if you are proficient with SQL. But otherwise a decent into to spark and nice flavour of data analysis with python.

By Eric J

Feb 9, 2017

Really good course to provide an overview of working within IBM's cloud platform offerings. This course provides the basics of ApacheSpark as well.

By Thomas M

Sep 12, 2020

Pretty fun introduction, assignments were moslty copy-paste from instruction videos, so you don't get to 'learn' the right way in my opinion

By Kevin A H L

Jul 30, 2020

I taught the course would be more advanced. Terminology is confusing at first, but besides that, the assignments aren't so challenging.

By Umer A B

Mar 18, 2017

The Grader template in the beginning is very confusing when doing first assignment. The response from Instructor should be quick.

By Mortaja A

Jan 4, 2019

structure and instruction to setup of ibm clound and ibm watson needs improvement. overall good instructions and flow.

By Tamer M

Sep 24, 2019

Most of the video's subtitles need to be synced, it was hard to fully understand the Indian accent without subtitles.

By Jaydeep K R

Jun 23, 2020

It was a good overview of the large scale data but I would be more interesting if they had provided more Practice.

By Norman F

Jan 13, 2019

Some errors like lambdas are not working anymore with Python, some typos like in Assignment 4.1 and missing steps.

By matthew w

Mar 15, 2021

Content (videos and quizzes were great). I would have preferred the coding assignments to be more challenging.

By Jithil S

Jul 5, 2020

A pretty good starter course for apache spark although the software version used in this course is outdated .

By Nicolas G J

Apr 8, 2021

The explanations sometimes are not clear, but with some readings and searching the projects can be resolved.

By Ricardo L

Jun 5, 2020

The content is good, very easy to pass. But too basic. You almost no learn anything about spark dataframes.

By Vinayaka S

Jan 21, 2021

Assignments need proper instructions. Also audio quality of lesson is not proper. Everything else is nice.

By Rodrigo V G

Aug 23, 2020

A very general review of Spark, Statistics and Data Visualization. Some great insights were given, tough

By Anand G

Jun 14, 2020

A good introduction to the steps to be taken to handle huge data sets. Surely would recommend to others.

By Braian G

Dec 24, 2020

I liked the course but it has some errors in the code, related to Python2 -> Python3. Good material!

By Zeynep İ

May 19, 2020

The course is perfect for beginners but some videos are old. They should be revised. Thank you :)

By Jeet K P

Aug 5, 2021

Maybe the course video should be changed properly. It will help student to understand properly

By Jeffrey G D

Jan 7, 2020

Some of the courses have out of date instructions, or the methods recommended are deprecated.

By Prithvi M

Mar 15, 2018

Good! Would have liked it even more if there was more data analysis involved using IOT data.

By Irfan H

May 14, 2020

The course lesson is easy enough to be learned, but I expect to learn more from this course

By Tim B H

Jan 2, 2021

Nice course on PySpark and Data Science. I rate it 4 Stars as some details were missing.