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

4.3
545 calificaciones
110 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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1 - 25 de 114 revisiones para Fundamentals of Scalable Data Science

por Mike D

Nov 29, 2018

Currently, it is not advisable to take this course.

I have finished the excellent IBM Data Science Professional Certificate series on Coursera and wanted to improve my knowledge of scalable Data Science with this series. Unfortunately, the videos and advice are extensively outdated. Python 2 is used through this course and the instructions of how to set up Node-RED and Cloudant do not work. I have been trying to work myself around that but then again, I wouldn't need this course in the first place and it only leads to confusion. Also, instead of the Cloudant application UI, Kibana seems to be used now, which there is no introduction to. I have noticed that Romeo Kienzler, the course lead, is very active and dedicated in the discussion forums. I am afraid, I have to give this course 0 stars for content (for now) and 5 stars for course lead dedication.

por David-Leigh B

Dec 18, 2018

IBM cloud environment is buggy and inconsistent with lectures.

When deploying services it sometimes fails and you are unable to remove them, rendering the account inoperable (as you have limits on free tier)

por Robert M

Jun 12, 2019

Training Videos are pretty good for a beginner but to consider this an advanced course is incorrect. Intermediate at most. In addition the application of lessons to assignments were minimal as the answers needed for the assignment were not related to the content that was discussed, just very simple fill in the blank.

por Marcin S

Apr 14, 2019

not enough additional materials

por Dmitry B

Jan 11, 2019

This course is teaching how to work with data in a distributed environment. While getting used to IBM Cloud takes time, it is definitely a friendlier environment for data scientists and it removes the burden of setting up the infrastructure.

por Zhihao Z

Jan 04, 2019

I couldn't find most relevant IBM web pages only with the instructions; I spotted typos and bugs in exercises; the most disappointing part is the autograder which malfunctions OFTEN on unclear grounds, I had to submit my assignment multiple times and to test the autograder.

I could have spent less time learning more.

por Vuong B A

Nov 30, 2018

Setup process is tedious

por Gabor K

Nov 10, 2018

I will un-enroll after 7 days in the course as the basic cloud environment setup did not work as written in the course handouts and videos. Which could be okay, however noone replied to my questions for 4 days on that, and the reply tips did not work either. Updating with screenshots, explanations no answer till today so what would have been a 15 minute job takes 7+ days here. At other coursera and competition platforms all my questions got answered in hours vs weeks as in this course.

por Vincenzo M

Apr 13, 2018

I'm really disapointed with the "Fundamentals of Scalable Data Science" course from IBM. The videos are referring to an outdated software releases, with really different screenshots from the ones existing on IBM platform. The discussions refers to code samples different from the ones available for download (flow2.js) and to applications present on the IBM Bluemix platform, without explaining where to found or how to create them. All these discrepancies make really difficult to follow the course. LBNL, the speaker is one of the most boring ever encountered in a webinar, barely able to read in english language. Being a course organized by IBM for such an important topic as Watson, I expected a much higher level of quality. I hope that the IBM staff will be able to perform a deep review of this series of course.

por Ozge Y

Jun 23, 2019

I find it unacceptable that the grader still had the same old problems from months ago. Adding notes directly to the python notebooks is not that difficult. #Return 4 significant digits, etc.

Plus, the grader output is not always useful. I execute the function in the python notebook, for whatever reason it does not fail, it works. The grader is more sensitive as it should be but it would be more meaningful at least it mentioned which line it has failed or which cell or which function.

The quizes during the videos seems a bit too random. I expect, if you are interrupting a video, you would be asking a question whose answer would be relevant for the later part of the video. Those pop-ups feels like unannounced midterm exams. There is already a full quiz section for this.

Perhaps my expectations were too high for this course.

por Nhan T N

Jun 21, 2019

The instruction is not so clear. Many mistake launch and grader does not run to score your submission.

por Roozbeh G

Jun 20, 2019

Well-taught course in an extremely important and sought-after data science field.

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 Dmytro T

Jun 18, 2019

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

por Tacio M D

Jun 11, 2019

Very good to follow. Instructor is very clear!

por JIN P

Jun 04, 2019

Thanks, really helps

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 Savan R

May 23, 2019

Covers exactly what is required for data science using spark in case IoT data applications and the fundamentals required for the advanced data science topics . I am happy with the course and the topics that I have learned so far!

por mohamed a

May 23, 2019

Assignment 2 need more clarficaiton

por ENRIQUE A C A

May 21, 2019

Excellent course

por Javier A C B

May 07, 2019

Great Job

por hamza j

May 01, 2019

Best course for People who have basic understanding about Python programming, Machine learning and statistics. The assignments are flexible and easy to complete. The course includes both theoratical and technical aspects of data science

por Paulo T P

Apr 27, 2019

awesome!

por Paulo R R

Apr 26, 2019

Awesome course!

por Jamiil T A

Apr 26, 2019

Excellent. I highly recommend it, jump in and enjoy learning the foundations.