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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:

26–50 из 445 отзывов о курсе Fundamentals of Scalable Data Science

автор: Igor E

4 мар. 2019 г.

Good course, but some of the later videos and assignments refer to data generation on Cloudant and NodeRed that made the videos confusing since the Cloudant videos were removed. This caused me to jump between the course and youtube videos to learn about data generation, only to find out it wasn't necessary.

автор: Miguel A B G

12 нояб. 2018 г.

Eeverything related with the graded assesment in this course fails, it's outdated and the practicla exercises are not well explain, if you are looking for a hard struggle to get very simple things done, this is your course

автор: Ramkumar K

6 апр. 2018 г.

Not so worth learning compare to the predecessor of this course. Should have included more assignment would have made the course very interesting.

автор: Vy D

25 янв. 2019 г.

Not enough coding, or I would like more interactive coding if that was possible in coursera. Or how would we do this like locally?

автор: Nicole Z K

13 янв. 2020 г.

Outdated content, with corrections as annotations in the videos. Not very engaging and has just a little of spark content.

автор: Ahmed E A T E

10 апр. 2019 г.

the content is really good but I don't understand the Indian accent well although this guy really did his best

автор: Mario R

14 июля 2019 г.

Need more exercises related to wrangling data and manipulating SQL's with apache spark

автор: shubham k g

4 июля 2019 г.

Nice but details are not discussed properly only taking names wasnt enough

автор: Andrés

7 февр. 2019 г.

Assigments needs to be better defined and explained

автор: Karthik D

19 янв. 2019 г.

Too many issues with lab material

автор: Ozge Y

23 июня 2019 г.

I find it unacceptable that the grader still had the same old problems from months ago. Adding notes directly to the python notebooks is not that difficult. #Return 4 significant digits, etc.

Plus, the grader output is not always useful. I execute the function in the python notebook, for whatever reason it does not fail, it works. The grader is more sensitive as it should be but it would be more meaningful at least it mentioned which line it has failed or which cell or which function.

The quizes during the videos seems a bit too random. I expect, if you are interrupting a video, you would be asking a question whose answer would be relevant for the later part of the video. Those pop-ups feels like unannounced midterm exams. There is already a full quiz section for this.

Perhaps my expectations were too high for this course.

автор: Roger S P M

23 янв. 2019 г.

Course content contains too much screen capture of clicking rapidly through IBM could menus. In most cases, the version of IBM Cloud now being deployed varies from the course, so students have to figure it out themselves.

Also, explanation of the tools and resources is very short - line one sentence. We are left to figure out what the tools are - cloudant and node-RED especially.

This course and certificate look like they should come after the first Data Science Certificate (9 courses). But there is a definite gap between the two. It is not clear what course is supposed to bridge that gap.

автор: Dan B

6 февр. 2019 г.

This course needs work. There needs to be more of a challenge, being an advanced course I expect a certain level of difficulty. I think the knowledge is too high level. There also needs to be more of a hands on approach. Let me connect to the Cloudent service, and more practice using spark and map functions.

автор: Jan

10 июля 2019 г.

Simply not on the same level as other ML Courses on Coursera. Programming assignments don't require you to do much by yourself. The bits you have to write, you have to guess from function names (no task description or anything is given).

автор: Suyash D

13 авг. 2018 г.

Very good course but codes and instructions are outdated. It needs serious improvement on that part. It is costing a lot more time to finish this simple course.

автор: Sheen D

1 сент. 2019 г.

Cannot understand what the instructor is saying half of the time... because he speaks really really fast...

автор: Thanh N N

20 июня 2019 г.

The instruction is not so clear. Many mistake launch and grader does not run to score your submission.

автор: Dorzhi D

27 янв. 2019 г.

Very fiddly. Video instructions do not correspond to IBM interfaces.

автор: Martí S C

8 дек. 2020 г.

I don't understand why the level was marked as advance

автор: Mateusz K

23 дек. 2018 г.

Quite outdated and chaotic

автор: Daya_Jin

27 сент. 2018 г.


автор: Sudesh A

22 сент. 2018 г.

While the course info describes this course as a beginner level, I would not describe it so. A lot of technical terms are thrown around without even saying a word about them let alone explain them.

The course is very disorganized, and the instructions for the assignments are not correct (and outdated). You have to basically figure out on your own how to set up the system before you even start doing the actual assignments. What you actually experience is completely different from what you see in the screenshots of the instructions.

This has been my experience just after being 2 weeks into the course. Hopefully things get better in the last two weeks. Honestly, so far I have only learnt a bunch of names.

I will update my review at the end of the course, if needed.

UPDATE: I eventually decided to unenroll from this course. This course is not worth it, in my opinion.

автор: Arman I

1 апр. 2021 г.

The lectures are quite useless. Assignments are almost irrelevant to Apache Spark. Estimated time for the course/assignments are so incorrect. You basically need 10mins instead of 3h to finish an assignment because there's only a couple of lines to fill in with your code.

автор: biern s

13 сент. 2020 г.

This is by far the worst.

The content is very poor so that 'advanced' should be removed.

In addition, the lecturer's English is unclear and not easy to understand, however, as there is empty content you don't need to worry.

I just wasted my money and time.

автор: man c y

4 июля 2019 г.

Corrupted assignment, you will never pass assignment 2 as the assignment checker was corrupted. so disappointed. in fact nice lecture and tutor and videos.