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Fundamentals of Scalable Data Science(으)로 돌아가기

IBM의 Fundamentals of Scalable Data Science 학습자 리뷰 및 피드백

4.3
931개의 평가
194개의 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 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 194개 리뷰 중 151~175

교육 기관: Ivan J M

Nov 02, 2019

There are a lot of not updated sections, sometimes it confuses me because in some videos he talks about how we will use Node RED but then we don't use it.

교육 기관: Lucas M

Dec 03, 2019

Seria ótimo se atualizassem o conteúdo do vídeo para reproduzir a versão atual do sistema e do Python, porém em teoria o conteúdo não deixou a desejar.

교육 기관: Eric J

Feb 10, 2017

Really good course to provide an overview of working within IBM's cloud platform offerings. This course provides the basics of ApacheSpark as well.

교육 기관: Umer A B

Mar 18, 2017

The Grader template in the beginning is very confusing when doing first assignment. The response from Instructor should be quick.

교육 기관: Mortaja A

Jan 05, 2019

structure and instruction to setup of ibm clound and ibm watson needs improvement. overall good instructions and flow.

교육 기관: Tamer M

Sep 24, 2019

Most of the video's subtitles need to be synced, it was hard to fully understand the Indian accent without subtitles.

교육 기관: Norman F

Jan 13, 2019

Some errors like lambdas are not working anymore with Python, some typos like in Assignment 4.1 and missing steps.

교육 기관: Jeffrey G D

Jan 07, 2020

Some of the courses have out of date instructions, or the methods recommended are deprecated.

교육 기관: Prithvi M

Mar 15, 2018

Good! Would have liked it even more if there was more data analysis involved using IOT data.

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: Revalino J C S

Jan 04, 2019

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

교육 기관: Suyash

Sep 23, 2019

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

교육 기관: Matthijs K

Feb 06, 2019

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

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: 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?