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Fundamentals of Scalable Data Science(으)로 돌아가기

IBM의 Fundamentals of Scalable Data Science 학습자 리뷰 및 피드백

4.3
1,020개의 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 151~175

교육 기관: 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

교육 기관: Xiang Y N

Apr 10, 2019

I was just wondering, is the content a bit short? Are there any more details on practising writing functions and text rather than an hour videoing and quiz? I believe intense programming skills practise is more efficient

교육 기관: Dipro M

Jul 18, 2019

Nice for a basic introduction. I really got to know a lot about the basics of 'data' and spark applications. However, the exercises and assignments seemed a bit too simple. Also could do with a few more extra readings.

교육 기관: Marcos P L

Dec 08, 2019

As an introductory course on data science and manipulation of large data sets, the course proved to be quite comprehensive and technically capable of leading the student to an understanding of all content.

교육 기관: Amy P

Aug 28, 2019

I learned a lot from this introduction and appreciated the amount of coding that the lecturer did during many of the videos. Would have liked more involved programming challenges at the end of each week.

교육 기관: Jan D

Mar 19, 2017

Good course with a good Instructor. It's a real basic course and good for beginners, though you need to have to dive into Python and Spark on your own to follow the course and the assignments. :)

교육 기관: Pranav N

Aug 28, 2019

Deserves 5 Star if the contents are updated such as removing redundant codes in Video lectures, upgrading Python and Spark to latest version etc. Overall a great place to start Scalable DS.

교육 기관: Bruno N

Sep 03, 2018

Very good course for a hands on overview introduction to the topic, and the associated tools (particularly Apache PiSpark).

Some issues with the auto grader encountered sometimes.

교육 기관: Gouri K

Nov 12, 2019

Good overall,instructor was very good,but I feel more examples could be used especially when explaining multidimensional vector space and such basics of graphs

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: 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: 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.