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學生對 IBM 提供的 Fundamentals of Scalable Data Science 的評價和反饋

1,970 個評分
441 條評論


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...




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.



Nice course. Learned the basics of a lot of different topics. Nice to do a large Data Science project in the last part. So you can apply all learned theory


301 - Fundamentals of Scalable Data Science 的 325 個評論(共 443 個)

創建者 matthew w


Content (videos and quizzes were great). I would have preferred the coding assignments to be more challenging.

創建者 Jithil S


A pretty good starter course for apache spark although the software version used in this course is outdated .

創建者 Nicolas G J


The explanations sometimes are not clear, but with some readings and searching the projects can be resolved.

創建者 Ricardo L


The content is good, very easy to pass. But too basic. You almost no learn anything about spark dataframes.

創建者 Vinayaka S


Assignments need proper instructions. Also audio quality of lesson is not proper. Everything else is nice.

創建者 Rodrigo V G


A very general review of Spark, Statistics and Data Visualization. Some great insights were given, tough

創建者 ANAND G 1


A good introduction to the steps to be taken to handle huge data sets. Surely would recommend to others.

創建者 Braian G


I liked the course but it has some errors in the code, related to Python2 -> Python3. Good material!

創建者 Zeynep İ


The course is perfect for beginners but some videos are old. They should be revised. Thank you :)

創建者 Jeet K P


Maybe the course video should be changed properly. It will help student to understand properly

創建者 Jeffrey G D


Some of the courses have out of date instructions, or the methods recommended are deprecated.

創建者 Prithvi M


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

創建者 Irfan H


The course lesson is easy enough to be learned, but I expect to learn more from this course

創建者 Tim B H


Nice course on PySpark and Data Science. I rate it 4 Stars as some details were missing.

創建者 Cosme B M R


The topics are difficult but the course is very good and the teacher is well qualified.

創建者 Mark B


Hard to follow at times... was able to get a lot of assistance in discussion forums

創建者 shubham b


Nice introduction to the differences between "normal and scaleable" data science



At first, I'm not sure what to do and it is hard for me to set up environment.

創建者 Deepshikhar T


The last quiz needs to be reviewed, otherwise awesome start to specialization

創建者 Eugene N


I actually loved this course because it helped augment my spark basic skills

創建者 Revalino J C S


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

創建者 Kaiqi Z


The assignment is a little bit simple, but the knowledge is quite helpful!

創建者 Suyash K T


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

創建者 Pablo R L


Too advanced material for introductory course. Excellent exercises.

創建者 Matthijs K


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