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

4.3
700 calificaciones
140 revisiones

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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 This course takes four weeks, 4-6h per week...

Principales revisiones

HS

Sep 10, 2017

A perfect course to pace off with exploration towards sensor-data analytics using Apache Spark and python libraries.\n\nKudos man.

MT

Feb 08, 2019

Good course content, however, some of the material especially the IBM cloud environment setup sometimes confusing

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126 - 141 de 141 revisiones para Fundamentals of Scalable Data Science

por Deepshikhar T

Sep 26, 2018

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

por Andrey O

Aug 11, 2018

Good course!

por Satyam K

Nov 20, 2018

This course gives you nice experience with Apache Spark. There is lot of update going on interface which creates few problem but discussion forum helps you out. Good for beginners in Data Science who have basic knowledge of python and SQL.

por Tinguaro B

Oct 04, 2018

Great introduction to Data Science on IBM Cloud.

por Dmytro T

Jun 18, 2019

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

por Christian M

Jun 20, 2019

It's an excellent course for anybody who wants to learn the basic of Spark, Watson Studio, and data analysis. It's also a good reminder for anybody well acquainted to the subject and want to know how to deal with it in Watson Studio

por Markochev S

May 27, 2019

I would like to thank the authors of this course. It gives great introduction into Apache Spark and its applications in real problems. The only thing I would like to notice is that assignments could be a bit more complicated. Writing any code from scratch is much better for a future Data Scientist than just 'fill in' gaps in the existing code.

por JIN P

Jun 04, 2019

Thanks, really helps

por Dipro M

Jul 18, 2019

Nice for a basic introduction. I really got to know a lot about the basics of 'data' and spark applications. However, the exercises and assignments seemed a bit too simple. Also could do with a few more extra readings.

por BAHADIR Y

Aug 16, 2019

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

por Pranav N

Aug 28, 2019

Deserves 5 Star if the contents are updated such as removing redundant codes in Video lectures, upgrading Python and Spark to latest version etc. Overall a great place to start Scalable DS.

por Amy P

Aug 28, 2019

I learned a lot from this introduction and appreciated the amount of coding that the lecturer did during many of the videos. Would have liked more involved programming challenges at the end of each week.

por Jorge A V

Jan 17, 2019

The idea and material behind the course is really interesting, albeit very basic. Some of the exercises and quizes, like the ones of interpreting plots are not very clear, since the plot quality is low. However, this is a very nice introduction to ML and IoT using Watson. Looking Forward for the next courses of the IBM Degree for advance data science

por Cesar R

Jul 06, 2019

Very basic lessons. Definitely what you would expect from an Advanced course.

por Nikhilanj P

Sep 06, 2019

Too many legacy issues. Would be better to start a new course altogether and maintain same syntax,etc.

por Csaba P O

Sep 09, 2019

The content was OK, but I have expected more. Probably it was too basic for me. I would have been happy to see some more real life examples, like when to use the different statistics to solve real problems, not only the theoretical ones.