Chevron Left
Fundamentals of Scalable Data Science(으)로 돌아가기

IBM의 Fundamentals of Scalable Data Science 학습자 리뷰 및 피드백

4.3
1,019개의 평가
216개의 리뷰

강좌 소개

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...

최상위 리뷰

AA

Jan 07, 2020

A very nice introduction to Apache Spark and it's environment. As a bonus, it's also a very nice refresher to your basic statistics!!! Great course!

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.

필터링 기준:

Fundamentals of Scalable Data Science의 215개 리뷰 중 176~200

교육 기관: Raj N

May 13, 2017

Great introduction to Data Science, IoT and scalable computing!

교육 기관: Dmytro T

Jun 18, 2019

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

교육 기관: Jonathan H

Feb 09, 2019

Good course, instructor was extremely knowledgeable.

교육 기관: Tinguaro B

Oct 04, 2018

Great introduction to Data Science on IBM Cloud.

교육 기관: Giovani F M

Dec 20, 2019

Great course to learn basic knowledge in spark!

교육 기관: EMMANUEL N

Apr 10, 2019

Nice course with good tutorials

교육 기관: Michal P

Mar 28, 2019

Very nice introduction

교육 기관: Elias L

Dec 31, 2018

Have been a good one!

교육 기관: JIN P

Jun 04, 2019

Thanks, really helps

교육 기관: Deleted A

Feb 11, 2019

Can I get a badge?

교육 기관: Ahmed T

Mar 10, 2019

Excellent :)

교육 기관: Andrey O

Aug 11, 2018

Good course!

교육 기관: Marvin L

Apr 02, 2020

it was good

교육 기관: ITALO D S L

Feb 29, 2020

Great

교육 기관: Nikhil P P

Feb 08, 2019

It was difficult to follow the IBM cloud setup since it was constantly changing, I couldn't understand the reason for using python2.7 since its only 10 months before it wont be supported by the community. Sometime instructors' pronunciations were not clear and and thus added extra confusion. However, instructor do actively participate in helping with discussions. Audio and video quality were also not very good. This course is a very basic introduction to IBM cloud and general stats. Prior knowledge of spark is useful. Overall the course is nice introduction to IBM cloud if one is interested.

교육 기관: Bayram

Feb 26, 2020

This is a very basic course even if it's my first interaction with Apache Spark. For sure, it gives some information. But I found the timeframes stated too long. You feel like you'll get a lot of information. But a week of videos and readings and assignments can be done in 1.5-4 hours depending on your experience how much time you spend on assignments.

Also, there are many materials that are outdated. That should be fixed if this course carries the name of IBM.

교육 기관: Eleni K

Oct 10, 2019

I was really looking forward to this specialization but from the very first course I am really disappointed. The videos refer to various not updated information and then suddenly we are expected to do an assignment that was not at all explained in the course. I am not saying it is difficult, or not achievable but to be honest until now (week 2) it feels mostly like a waste of time.. Really sorry for this review.

교육 기관: 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

교육 기관: Dmitry S

Mar 10, 2020

The course is called 'Fundamentals' and is indeed pretty basic. A good quick overview of the most basic concepts. Sometimes too basic to qualify for an Advanced course on Coursera. So, not really clear for which audience the course is.

Another fundamental course that does a better job is Spark Fundamentals from cognitiveclass.ai.

교육 기관: Tony H

Nov 04, 2019

I felt that, for a course labelled as 'Advanced', there were too many trivial questions in the quizzes and too much hand-holding in the programming assignments. That being said I did enjoy the course and learned quite a lot and look forward to the next one in the specialisation.

교육 기관: Mohamed A T

Jan 29, 2020

The course was great, the material and the assignments.

IBM Watson platform was easy to use.

But I can't see how this course is included in the "advanced" data science specialization.

Honestly I was expecting a more advanced course. But we'll see with the next ones.

교육 기관: 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.

교육 기관: Kaiwalya

Mar 21, 2020

The course content is amazing but the instructor's accent is very difficult to understand and in some videos subtitles in English weren't available.

교육 기관: BAUDRY S

Nov 20, 2019

The functions we need to complete looks quite messy, it'a little bit overwhelming especially for people who start with spark.

교육 기관: Mohamed M

Apr 05, 2020

the assignment is required to be in sparkaql functions however the course is just using spark with built in functions