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Fundamentals of Scalable Data Science(으)로 돌아가기

IBM의 Fundamentals of Scalable Data Science 학습자 리뷰 및 피드백

4.3
별점
1,549개의 평가
329개의 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

GA

May 06, 2020

Its a great experience especially with this course. I appreciate Romeo the way he designed the assignments. It brings out the clear understanding.

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 329개 리뷰 중 251~275

교육 기관: Mark B

Apr 17, 2020

Hard to follow at times... was able to get a lot of assistance in discussion forums

교육 기관: BAHADIR Y

Aug 16, 2019

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

교육 기관: Deepshikhar T

Sep 26, 2018

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

교육 기관: Eugene N

May 12, 2020

I actually loved this course because it helped augment my spark basic skills

교육 기관: Revalino J C S

Jan 04, 2019

The environment setup is a little cumbersome due to constant changes in UI.

교육 기관: Kaiqi Z

Apr 05, 2020

The assignment is a little bit simple, but the knowledge is quite helpful!

교육 기관: Suyash

Sep 23, 2019

There are a lot of glitch with the assignments, hope it gets fixed soon

교육 기관: Pablo R L

May 23, 2020

Too advanced material for introductory course. Excellent exercises.

교육 기관: Matthijs K

Feb 06, 2019

Sets you up well for working with Spark within the IBM Environment.

교육 기관: Tushar J

Jul 14, 2020

Good course. The pace was good and the material was enough for me.

교육 기관: Yifei Z

Apr 11, 2020

Assignments are too simple -- too similar to the course material.

교육 기관: Harsh D

Feb 03, 2019

Quite Good. But sometimes i had trouble following instructions.

교육 기관: Raj N

May 13, 2017

Great introduction to Data Science, IoT and scalable computing!

교육 기관: Abhay B K M

Jul 03, 2020

It is hard to follow as it is very advanced and unevenly paced

교육 기관: ANUBHAV M

Apr 27, 2020

More interaction with the instructor would be appreciated.

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: JunYeol L

Jun 26, 2020

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

교육 기관: Atif A G

Jun 10, 2020

Good Course but could have had a lot more detail.

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: Akash S

Jul 04, 2020

Good course, but assignments are a bit easy

교육 기관: Rong L

Jul 18, 2020

The instructor can be a bit slower.

교육 기관: EMMANUEL N

Apr 10, 2019

Nice course with good tutorials

교육 기관: Michal P

Mar 28, 2019

Very nice introduction