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学生对 IBM 提供的 Fundamentals of Scalable Data Science 的评价和反馈

4.3
534 个评分
109 个审阅

课程概述

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...

热门审阅

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

筛选依据:

1 - Fundamentals of Scalable Data Science 的 25 个评论(共 110 个)

创建者 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.

创建者 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)

创建者 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.

创建者 Marcin S

Apr 14, 2019

not enough additional materials

创建者 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.

创建者 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.

创建者 Vuong B A

Nov 30, 2018

Setup process is tedious

创建者 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.

创建者 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.

创建者 Dmytro T

Jun 18, 2019

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

创建者 Tacio M D

Jun 11, 2019

Very good to follow. Instructor is very clear!

创建者 JIN P

Jun 04, 2019

Thanks, really helps

创建者 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.

创建者 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!

创建者 mohamed a

May 23, 2019

Assignment 2 need more clarficaiton

创建者 ENRIQUE A C A

May 21, 2019

Excellent course

创建者 Javier A C B

May 07, 2019

Great Job

创建者 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

创建者 Paulo T P

Apr 27, 2019

awesome!

创建者 Paulo R R

Apr 26, 2019

Awesome course!

创建者 Jamiil T A

Apr 26, 2019

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

创建者 Uzwal G

Apr 26, 2019

Thank you

创建者 Pawel P

Apr 23, 2019

Too easy to be called advanced. I look forward to seeing what's next.

创建者 Daniel T

Apr 21, 2019

Be careful when signing up for your IBM Cloud Instance and remember to shut it down when you're not using it. I ran out of free hours and unfortunately they're no longer free after the first 30 days which either makes it impossible or expensive to finish this course. Also, 30 days might mean an arbitrary 30 day billing cycle, perhaps starting on the 1st of the month.

创建者 ASHISH J

Apr 15, 2019

awesome course, got a good understanding of statistics in an intuitive manner.

The main strength of this course is that, this course will help you to develop intuition of the whole data science concepts into the real world scenario.