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学生对 IBM 提供的 Fundamentals of Scalable Data Science 的评价和反馈

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388 条评论


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: 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 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 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... This course takes four weeks, 4-6h per week...


Jan 6, 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!

May 5, 2020

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


201 - Fundamentals of Scalable Data Science 的 225 个评论(共 389 个)

创建者 alexander n

May 16, 2020

Great course!

创建者 Felipe P B

Aug 9, 2019

Great course!

创建者 Alejandro S M

Mar 25, 2019

Just awesome!

创建者 Aymen R

Jun 30, 2020

good course!


Feb 8, 2020

Great course

创建者 Zeghraoui M

Mar 26, 2019

I loved it !

创建者 Vishwanath b

May 27, 2020

best course

创建者 Farrukh N A

Apr 24, 2020

Good Course

创建者 Ranjith K M

Nov 30, 2020

Very good

创建者 bhargav d

Sep 27, 2020


创建者 Anand M

Jun 23, 2020

very nice


Jun 8, 2020

very nice

创建者 Lahcene O M

Apr 4, 2020

Great job

创建者 Charles-Antoine d T

Oct 10, 2019

very good

创建者 Javier C

May 7, 2019

Great Job

创建者 Uzwal G

Apr 26, 2019

Thank you

创建者 Alessandro R M

Jan 5, 2019


创建者 Ahmad e D

Nov 12, 2020


创建者 Thiago P

Apr 27, 2019


创建者 ARUL N J

Sep 29, 2020


创建者 Jeff L J D

Jan 23, 2021


创建者 Dhaou B

Jan 1, 2021


创建者 Venkadesh

Nov 27, 2020


创建者 Yash V

Sep 8, 2020


创建者 Sakshi U

Jul 24, 2020