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

IBM의 Fundamentals of Scalable Data Science 학습자 리뷰 및 피드백

4.3
별점
1,435개의 평가
309개의 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 312개 리뷰 중 201~225

교육 기관: am

Apr 14, 2017

Nice Course. Going straight forward to the manipulations using spark, and giving a great overview on how to deal with IoT data in the Cloudant NOSQL platform. Would hope to see a new course where we can use MLLIB with massive IoT data to showcase the power of parallel programming!

교육 기관: Sunil M

Apr 17, 2017

I wish this was more extensive /detailed course and assignments little bit more complex. The moderator timely response was greatly lacking. If the course instructor is asking the students to try out RDD while the auto-grader depends on SQL, it should have been clarified.

교육 기관: Hoàng M T

May 01, 2020

Nice course. Inform the basic concepts of statistics.

Some of the code is not consistent (E.g. the week 4 assignment I have to remove the parameter of getListForHistogramAndBoxPlot() and getListsForRunChart() in submit cell in order to successfully submit).

교육 기관: Dushyant R T

Jun 15, 2020

The course was designed some years ago and now it needs some update considering the technology has changed a bit. Even after all of that, the teachers are really good and they provide high-quality education. Really glad I could be part of this course.

교육 기관: Satyam K

Nov 20, 2018

This course gives you nice experience with Apache Spark. There is lot of update going on interface which creates few problem but discussion forum helps you out. Good for beginners in Data Science who have basic knowledge of python and SQL.

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: Udbhav S P

Apr 11, 2020

there were two errors i noticed if you could correct them - check the last assignment in the grading system it has parameters given which are not required and the last quiz there is a ques about PCA pls correct the options

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: Víctor M P

Apr 30, 2020

El curso es una introducción muy básica, lo más interesante son los ejercicios opcionales como el de node-red. Me esperaba que se aplicaran buenas prácticas en los ejercicios, pero como introducción está bien.

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: ADEJOKUN A

Jun 24, 2020

Great Introductory course for Big Data Analytics. The exercises and the assignments had the appropriate level of difficulty considering this was an advanced course. Thank you IBM and Coursera.

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: Daniel D S P

Jun 07, 2020

La semana 2 es un ladrillo, se explican los temas de ingeniería para el procesamiento masivo de datos, pero la explicación no es muy pedagógica que digamos. Por lo demás estuvo muy bien.

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: Quazi M T M

Jul 05, 2020

There should be some links that are helpful towards this course, as it is an intermediate course, what courses are available in Coursera prior to this as a beginner lesson.

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: Gerardo E G G

Jun 26, 2020

Great Course!

I would like to suggest to update the videos in order to reflect the operations in Python 3.x rather than 2.x but everything else was great!

교육 기관: Mohammad M A

May 10, 2020

Romeo is a great instructor and I love his lectures, however some of the quiz questions are very trivial and aren't explained on his video tutorials...

교육 기관: Lucas M B

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.