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Avis et commentaires pour d'étudiants pour Fundamentals of Scalable Data Science par Réseau de compétences IBM

2,006 évaluations

À propos du cours

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...

Meilleurs avis


13 janv. 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.


21 juil. 2021

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

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426 - 450 sur 450 Avis pour Fundamentals of Scalable Data Science

par Paulo R C D S

4 mai 2020

Very basic and Spark exercises are too easy to learn useful skills

par Yew C L

15 oct. 2020

Not really fundamental. Beginner will have difficulty to learn.

par Nima

4 juin 2020

Big data materials are less discussed specially coding sections


21 août 2020

The course feels old now. Not much interactive.

par Hossein A

17 juin 2020

Very good topics very not very good instructors

par Smriti C

8 juin 2020

Not a recommended course

par Darragh K

30 mai 2022

The whole course seems to be mainly an advertisment for IBM Watson Studio. However, there are caveats in using the IBM service: Firstly, the instructions given in the course are outdated, and setting up the environment is quite cumbersome. Secondly, the free IBM cloud lite licence allows the usage of 10 Capacity Unit Hours (CUHs) per month. However, the environment that can be used for this course uses 1.5 Capacity Unit Hours (CUH) per hour. This is just not enough to provide a proper learning environment. All in all I found this course to be a bit of an embarrassement for IBM.

par Georgia C

1 sept. 2021

An introduction into incredibly basic data science concepts and the assignments are very simple. Would like a more in depth coverage of Apache Spark, including how to use it outside of the Watson Studio set up. I found the material on parallel computing quite complex and hard to follow. Some material has been removed from the course which makes the videos in week 2 seem a bit incongruous.

par Felipe M

18 sept. 2019

Videos are old. It feels like he had a bunch of material and put them together to create this course. For example: There are assignments that they give you the answer because the questions are not supposed to be there. He doesnt teach, instead, he reads a script. The assignments are not challenging and you dont feel like you learned. Horrible and painful.

par Gerardo M

10 juin 2020

A lot of the code explained in the video doesn't work with Python 3. The course is missing real examples with updated code working with the latest versions. If I have to go on the internet to learn how to pass each programming assignment of this course because the videos are outdated then I can do this for free, no need to pay the 40 euros/month. Thanks

par Polina B

20 févr. 2022

The course does not correspond to the name "Advanced" Data Science at all. Instead of watching the videos about what mean and standard deviation are, I expected to get a more structured and detail view on what Spark is and how it works. Also, there are some typos and mistakes and creators do not put much effort on keeping the materials up to date.

par Oriol-Boris M F

12 oct. 2022

The content is out of date, the IBM webpage has changed and it is impossible to follow the instructions, many link don't work anymore. Plus it ask you to use an environment that you are suposed to create in the video 5 but that video does not exist, what a mess

par Deleted A

12 nov. 2020

Course materials is not up to the with the latest state of the IBM Cloud environment. IBM Cloud environment is super buggy. Need to transform this training to make the user use its own environment and not push the IBM Cloud infrastructure.

par James N

1 août 2022

Covers about 30 seconds worth of actual content. If you know anything about Python/stat, this course doesn't give you anything about *scalable* with exception to a super high level presentation of the idea behind Spark.

par Bin W

8 mars 2022

The IBM cloud is constantly changing but the taching materials are always out dated, on Discussion Forum, they either don't reply to my question more than 2 months, or gave me technically correct but useless answers.

par Vladyslav M

5 juil. 2020

не можу зареєструватись за посиланням, будь ласка, перевіряйте справність всіх ресурсів перед тим, як публікувати курс. дойшов до практичного заняття і не зміг зареєструватись.

par ashwani b

4 avr. 2020

Structure and flow is the reason people pursue online courses then studying from any random youtube video tutorials. This course lacks those basic properties. Major concern was to promote IBM cloud than to teach.

par GARG M

27 oct. 2021

Well I have taken several courses on coursera and their explaination was pretty good but in this course explaination was not up to the mark , very disappointed.

par Ahmet Y

17 mars 2020

After the IBM Data Science Proffesional Specialization this course was very inadequate. Lambda calculus is not explained well.

par Mike H

1 janv. 2020

Not well structured in my opinion. Difficulty of content not well balanced. Outdated presentations and content...

par Goce Z

19 mai 2020

easier to just make it labs and some reading as all the videos are just watching the instructor type code

par Kaustav S

14 mai 2020

Not a course relevant to data science, what needed in the market perspective

par W L

20 sept. 2020

course material is inconsistent and not well prepared.

par Sergei B

26 août 2020

To easy to be advanced ML course.

par jack g

29 avr. 2021

content needs updating.