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

4.3
étoiles
1,933 évaluations
426 avis

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: https://www.coursera.org/specializations/advanced-data-science-ibm 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 ibm.biz/badging. 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 https://www.coursera.org/learn/sql-data-science 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... https://cognitiveclass.ai/learn/spark https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/f8982db1-5e55-46d6-a272-fd11b670be38/view?access_token=533a1925cd1c4c362aabe7b3336b3eae2a99e0dc923ec0775d891c31c5bbbc68 This course takes four weeks, 4-6h per week...

Meilleurs avis

ZS
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.

MA
19 juin 2021

Great Course but this would have been even a better course if more concepts and details were covered in it. Anyways, still a great course for beginners

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226 - 250 sur 429 Avis pour Fundamentals of Scalable Data Science

par BHARGAV D

27 sept. 2020

excellent

par Anand M

23 juin 2020

very nice

par STREETS O I

8 juin 2020

very nice

par Lahcene O M

4 avr. 2020

Great job

par Charlie d T

10 oct. 2019

very good

par Javier C

7 mai 2019

Great Job

par Uzwal G

26 avr. 2019

Thank you

par Alessandro R M

5 janv. 2019

excellent

par Ahmad e D

12 nov. 2020

🔥🔥🔥🔥

par Thiago P

27 avr. 2019

awesome!

par ARUL N J

29 sept. 2020

Nothing

par Jeff D

23 janv. 2021

THanks

par Dhaou B

1 janv. 2021

Thinks

par HAPPY J

5 sept. 2021

Nice

par Sivanta S

25 juil. 2021

nice

par Venkadesh

27 nov. 2020

good

par Yash V

8 sept. 2020

Good

par Sakshi U

24 juil. 2020

nice

par Rifat R

14 juil. 2020

Good

par Ankit M

1 déc. 2019

good

par Sơn T

15 juil. 2021

p

par Waleed M S A A A G

8 févr. 2019

ز

par Guido P

3 mai 2020

The first course "Fundamentals of Scalable Data Science" on the specialization "Advanced Data Science with IBM" provides a good overview on theory, methods and tools you need for larg-scale data analysis. It requires basic to intermediate knowledge of Python and math. But it helps if you have experience beyond that to understand some ideas quicker and get the broader context.

Potential learners should know - as it is the normal thing with teaching/learning something - the teachers can't teach you something; you have to learn it. Means: spent some time beyond the time you need to consume the material from coursera. For example, I wrote five pages on the basics on statistics. It really helps! Again, the teachers organize a well well structured journey through the course material, but the just point to things that might be interesting.

On recommendation/request for improving quality of the provided videos: the are quite outdated. Date back to 2016/2017 and use Python 2 (which is not longer maintaned since 2020). Using the old python isn't too much of a problem, but it certainly does not help to learn effectively. The bigger problem is that the shown code is massively annotated with corrections and updates. These are all correct and helpful. But simply creating an updated video is way easier to consume. Just image a studend would submit his/her thesis as a draft plus a chain of 3 patches that have to applied on the thesis draft version. Not too handy, uhhm!?

par Alfredo P

6 mars 2020

My 4-star review is based on the many errors the course has. The material s great and the instructor is very knowledgable and seems to be on top of the class, however, I did not get a single reply of the notes I posted in the forum.

Besides the structure, the class requires revision due to inconsistencies and errors. It is surprising that topics have not been updated after many comments in the discussion forum.

Overall for me, it was a great experience and great learning experience

par Scott B

2 mai 2020

The content is great and applicable to industry. My only critique is that the coding assignments had been too simple. I would have preferred less hand-holding and more examples to work through to ensure the learner truly conceptualizes the process. With that said, it is easy enough for a learner to apply the process to other applications and understand how the pieces fit together for more real-world application.