Chevron Left
Volver a Fundamentals of Scalable Data Science

Opiniones y comentarios de aprendices correspondientes a Fundamentals of Scalable Data Science por parte de IBM

1,906 calificaciones
420 reseña

Acerca del Curso

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...

Principales reseñas

13 de ene. de 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.

25 de mar. de 2021

It's good but it really requires someone who knows and even master Spark Apache(+SQL fundamentals) so that you can follow and understand and take advantage of the course

Filtrar por:

326 - 350 de 421 revisiones para Fundamentals of Scalable Data Science

por Dmytro T

18 de jun. de 2019

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

por Jon H

9 de feb. de 2019

Good course, instructor was extremely knowledgeable.

por Hunter P

11 de may. de 2021

Great course! Could delve deeper into more topics.

por JunYeol L

26 de jun. de 2020

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

por Atif A G

10 de jun. de 2020

Good Course but could have had a lot more detail.

por Tinguaro B

4 de oct. de 2018

Great introduction to Data Science on IBM Cloud.

por Giovani F M

20 de dic. de 2019

Great course to learn basic knowledge in spark!

por Akash S

4 de jul. de 2020

Good course, but assignments are a bit easy

por Francesco C

25 de feb. de 2021

Good explanation. Perfect starting course.

por Rong L

18 de jul. de 2020

The instructor can be a bit slower.


10 de abr. de 2019

Nice course with good tutorials

por Heyimeng

21 de oct. de 2020

i think it is a bit too simple

por Caner B B

19 de nov. de 2020

please include more practice

por Michal P

28 de mar. de 2019

Very nice introduction

por Elias L

31 de dic. de 2018

Have been a good one!

por jin p

4 de jun. de 2019

Thanks, really helps

por Deleted A

11 de feb. de 2019

Can I get a badge?

por Bladimir P

24 de sep. de 2020

Great course!

por Ahmed T

10 de mar. de 2019

Excellent :)

por Andrey O

10 de ago. de 2018

Good course!

por Marvin L

2 de abr. de 2020

it was good

por Fernando P

2 de oct. de 2020

Very good!

por Caroline L

27 de abr. de 2021

Too easy.

por Italo L

29 de feb. de 2020


por Carlos F

29 de abr. de 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.