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Learner Reviews & Feedback for Fundamentals of Scalable Data Science by IBM

4.3
stars
1,906 ratings
420 reviews

About the Course

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...

Top reviews

ZS
Jan 13, 2021

The contents of this course are really practical and to the point. The examples and notebooks are also up to date and are very useful. i really recommend this course if you want to start with Spark.

AE
Mar 25, 2021

It's good but it really requires someone who knows and even master Spark Apache(+SQL fundamentals) so that you can follow and understand and take advantage of the course

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251 - 275 of 421 Reviews for Fundamentals of Scalable Data Science

By Markochev S

May 27, 2019

I would like to thank the authors of this course. It gives great introduction into Apache Spark and its applications in real problems. The only thing I would like to notice is that assignments could be a bit more complicated. Writing any code from scratch is much better for a future Data Scientist than just 'fill in' gaps in the existing code.

By Madison H

Apr 20, 2020

the material in this course was interesting and I learned a lot in a short time. I now understand how to deal with big data using Spark which is exactly what I wanted. One thing I wish was different was the code in the submission notebooks. I wish the functions we wrote had parameters for example instead of basically just running a script.

By Ahmad R J

Nov 23, 2019

I liked the course because it introduced me to new topics but it did not really go further as expected from an advanced specialization. Maybe when I finished other courses, I find out that it well prepared me for the rest. However, please provide more sample datasets, similar questions, and generally more practice.

By Jarryd

Mar 8, 2020

A very slow beginning although that is to be expected so that the course can draw in people from a wide range of backgrounds. Still a little tedious for someone with a little more of a background. Very well organized and it seems like a great introduction to Spark / Pyspark for those just beginning with this tool.

By Shubham S

Mar 10, 2019

The course is quite good. However, its not meant for absolute beginners. One needs to have a decent understanding of Python and SQL in order to follow the course and complete the programming assignments. However, the extra effort put towards learning how to program is well worth it

By 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!

By 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.

By Hoàng M T

May 1, 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).

By Igor O

Sep 1, 2020

It's a good course, good practices of IBM Watson Studio, Apache Spark and Python programming skills. Although would like to see more specific content about data science like methods and linear algebra libraries and techniques. But it was satisfatory, btw.

By 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.

By Victor W

Oct 31, 2020

Good course. However, there are a lot of silly mistakes in the videos, which is solved by "cloud text boxes". Does not look professional, rather re-record the videos. The videos are sometimes also pixelated. This could be improved significantly

By 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.

By 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

By Udbhav 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

By 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

By 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.

By 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.

By Marcos P L

Dec 8, 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.

By 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.

By William Y

May 5, 2021

I wish the course offers more information on SparkContext and SparkConf, setMaster, wget, etc; In other word, how data is being passed around, and what component is responsible for what tasks, etc.

By 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. :)

By 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.

By Pranav N

Aug 27, 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.

By Daniel D S P

Jun 7, 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.

By Bruno N

Sep 3, 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.