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Вернуться к Fundamentals of Scalable Data Science

Отзывы учащихся о курсе Fundamentals of Scalable Data Science от партнера IBM Skills Network

Оценки: 1,977

О курсе

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...

Лучшие рецензии


13 янв. 2021 г.

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 июля 2021 г.

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

Фильтр по:

426–445 из 445 отзывов о курсе Fundamentals of Scalable Data Science

автор: Hossein A

17 июня 2020 г.

Very good topics very not very good instructors

автор: Smriti C

8 июня 2020 г.

Not a recommended course

автор: Darragh K

30 мая 2022 г.

T​he 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.

автор: Georgia C

1 сент. 2021 г.

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.

автор: Felipe M

18 сент. 2019 г.

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.

автор: Gerardo M

10 июня 2020 г.

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

автор: Polina B

20 февр. 2022 г.

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.

автор: Deleted A

12 нояб. 2020 г.

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.

автор: James N

1 авг. 2022 г.

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.

автор: Bin W

8 мар. 2022 г.

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.

автор: Vladyslav M

5 июля 2020 г.

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

автор: ashwani b

4 апр. 2020 г.

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.

автор: GARG M

27 окт. 2021 г.

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.

автор: Ahmet Y

17 мар. 2020 г.

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

автор: Mike H

1 янв. 2020 г.

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 Outdated presentations and content...

автор: Goce Z

19 мая 2020 г.

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

автор: Kaustav S

14 мая 2020 г.

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

автор: W L

20 сент. 2020 г.

course material is inconsistent and not well prepared.

автор: Sergei B

26 авг. 2020 г.

To easy to be advanced ML course.

автор: jack g

29 апр. 2021 г.

content needs updating.