学生对 IBM 提供的 Python for Data Science, AI & Development 的评价和反馈
课程概述
热门审阅
HK
Oct 19, 2022
This was an extremely informative course and I believe is perfect way to strt off your coding journey. The teaching style was understandable.detail oriented and very practical. Highly Recommended.
PJ
Nov 30, 2020
It is a good course and teaches with the basic of Python so that anyone can understand it very well. Videos are good and can easily be understandable to anyone who is new to Python and Data Science.
5701 - Python for Data Science, AI & Development 的 5725 个评论(共 7,836 个)
创建者 Yacine B
•Jul 30, 2024
the course Covers all the basics of python and data structure but i think the course is not for absolute beginners.
创建者 Muralikrishnan R
•Feb 20, 2020
Quite tough for a beginner, as there are a lot of things to integrate within short videos.
But all in all very good.
创建者 Filipe S M G
•Aug 22, 2019
Interesting initial applications for Data Science using Python and Jupyter.
OBS: The videos had many small mistakes.
创建者 David v d Z
•Jul 29, 2019
Pretty nice course, very elementary though. Only follow if you're a real beginner, with no knowledge of programming.
创建者 Frank H
•Jul 16, 2023
IP good, but some notebooks didn't work and contained some minor errors - it looks like some content is deprecated!
创建者 Brian B
•Nov 24, 2020
Good crash course of Python specifically for data science usage, including python syntax, data structures, and APIs
创建者 Hridoy D M
•Mar 30, 2025
Great course. It would be better to add some exercises for web scraping and how to get the data from the web site.
创建者 atefe t
•Oct 12, 2024
It was a good course. But now I can not verify my id to get the certificate with my name. Please help me to fix it
创建者 Islam S
•Dec 16, 2020
I tried cracking in Python several times, and I think I can say this has been the best introduction I've ever had.
创建者 Chloe H
•Apr 18, 2020
pro: practice studio and quiz are very helpful in learning
con: videos are too fast and short, not a lot of content
创建者 Samrat P
•Feb 2, 2020
Decent Course but a bit fast-paced so you need to very attentive and if possible try to do MSDN's Course First !!!
创建者 arkopravo b
•Sep 25, 2019
i learn new skill from this course .so i really thankful to coursera. i recomend everybody to learn form coursera.
创建者 LEANDRO M
•Sep 17, 2023
The course is quite easy and covers the concepts not in too much detail. Nevertheless, the explanations are good.
创建者 Suhas S
•Mar 2, 2021
Great course for beginners. Could be better if we could have got more and more programming examples in the videos
创建者 Shivnaesh k
•Apr 27, 2020
The course content was very good and knowledgeable, easy to follow, and well framed. Thank you Coursera and team.
创建者 le u
•May 7, 2023
This course is amazing as I've learnt different python libraries through working with some small scale problems.
创建者 vaishali k
•Jul 31, 2022
The practical knowledge provided by this course is very good.But sometimes the lab environment doesnot responds.
创建者 Pratik K
•May 13, 2022
Basic are covered really well, but few topics like web scrapping looks like bit discoonected from current course
创建者 Shalvi P
•Aug 19, 2019
Very Intresting course and after doing this course my knowledge about python and data science raises very much.
创建者 Maria C B R
•Jul 2, 2025
Es un buen curso, pero muy abrumadora y extensa, debes de tener mucha paciencia para poder completar este curso
创建者 Divyansh D
•Jun 23, 2025
could use better labs, most labs that need to download and use a specific file from IBM servers just don't work
创建者 Tejal P
•Sep 28, 2022
Rest API and Webscrapping felt difficult while learning. Difficult to understand. Please give as many examples
创建者 Carlos b
•Jun 28, 2021
Muy Bueno, La parte de Python enseña mucho, se deberia potenciar el Web scraping, creo que fue demasiado básico
创建者 Carlos P
•Jan 28, 2020
The final project was a bit disappointing, it was too easy and didn't cover much of the material of the course.
创建者 Nikhil C C
•Oct 21, 2019
Everything is IBM Watson. Please reduce IBM product recommendation and let us learn concepts to apply anywhere.