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
TM
Nov 17, 2019
it becomes easier wand clearer when one gets to complete the assignments as to how to utilize what has been learned. Practical work is a great way to learn, which was a fundamental part of the course.
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.
201 - Python for Data Science, AI & Development 的 225 个评论(共 7,678 个)
创建者 Brian G
•May 21, 2019
Very comprehensive! like the labs a lot!
创建者 Mustapha A
•May 31, 2019
Great Python Course From Zero to Hero.
创建者 Chandan S
•May 11, 2019
Brilliant course for beginners.
创建者 Ashwani
•May 14, 2019
Such a nice iinstructor it was
创建者 Raghvendra S
•May 26, 2019
great learning experience..!!
创建者 Sharan K
•May 15, 2019
Good introductory course
创建者 Sriram R
•Jun 2, 2019
Great for a beginner
创建者 Dr.Soumik P
•Nov 12, 2023
Excellent to learn
创建者 George M
•Oct 10, 2023
Very good course
创建者 Kamal S D
•Oct 28, 2020
awesome course
创建者 Md A A
•May 28, 2019
Awesome lesson
创建者 Muhammad S K
•Jul 6, 2022
very good.
创建者 Hamid R B
•May 14, 2019
Very good.
创建者 Nitish K S
•May 23, 2019
all awsm
创建者 Chironjeet K C
•May 26, 2019
Great
创建者 Sam
•Nov 21, 2024
The structure is excellent, with videos, readings, and quizzes. The labs are a great way to practice the material learned in the videos and readings. Additionally, the breadth of content is great. I feel like it covers a great amount of Python to get started on your first projects. That said, there are a lot of errors in the material and the labs. I reported most as I came across them, but it can be frustrating when something is explained incorrectly or you are given contradictory information. There are many grammatical mistakes in the lab explanations, as well. The mistakes do not ruin the course, as most of the information is phenomenal, and a lot of detail is packed in. However, it significantly hurts the experience and makes the process frustrating. This is on top of the frustration of labs including code that is not explained. There are some functions used in the sample code, and keywords used, that are not explained in comments or the lab preamble. Maybe the idea was not to overexplain, but I found this is very frustrating when it happened. All that said, this course is still worth 4 stars. It's a lot of information with a lot of resources given. I'm glad I took the course (although with the caveat that it was free since I completed it during the 7-day free Coursera Plus trial).
创建者 Ruofei F
•Sep 2, 2024
It is very fundamental and easy and simple at the beginning. The lecture and lab are not easy to understand for beginners regarding pandas/numpy, APIs, and web scraping. The lab and exams have some errors. When learners post on the forum, the staff who answered questions keep asking for screenshots or more details or share with GitHub. Incredibly, the staff who are responsible for answering the questions are not familiar with the course content. It is easy to locate the exam questions. Also, it is easy to figure out that the lab has errors because BeautifulSoup needs to parse data from HTML and when you install and import html5lib, you should use it as BeautifulSoup(s, "html.parser") instead of soup = BeautifulSoup(s, "html5lib"). I don't understand why someone responsible for answering the questions is not even familiar with the course content.
创建者 Dawna B
•Aug 29, 2022
This course was an uphill climb. There were many concepts and programming pieces that I did not know. I was able to follow the programming pieces and understand how to "read" the script. Staying on track with the theory allowed me to gain a great basic foundation into Python. Since I am not a data scientist or engineer, I don't think I need to know Python deeply. I do look forward to undersanding what level of Python will be useful as a data analyst.
I did feel that some of the answers may have been incorrect on the quizzes. I saw some information on that in the Q&A of other participants. It would have also been nicer to have the Python level objective stated more clearly that a participant will see a much deeper level than their beginning knowldge and to digest the understanding over the techinical in some of the learning.
创建者 Jon M
•Mar 5, 2024
Great for foundational learning. Modules 1-4 give you a great understanding of how data flows in Python, while module 5 is kind of a mess. Importing and using random things to complete a "learning" task without explaining why we're using those left a hole in the knowledge path where the foundation of the module felt shaky throughout. I'll make it up on YouTube, but I shouldn't have to. I will say again, that the first 4 modules of this course are on point and are well worth it but you won't walk away from this course as a programmer. I'm walking away understanding how to read the data flow in the program with confidence and knowing exactly what I need to study next to maximize my analysis.
创建者 Julie B
•Jul 10, 2024
The "Python for Data Science, AI & Development" course comprehensively covers essential topics for aspiring data scientists and AI developers. Its well-researched and informative material is particularly valuable for those with some programming experience. However, the mixed format of videos, written notes, and labs can make the content feel disjointed and scattered, highlighting the need for better structure and more hands-on exercises. Complete beginners may need additional external resources and practice apps to fully understand the concepts. Overall, the course provides a solid foundation for further exploration in data science and AI.
创建者 Nobile T
•Jul 24, 2024
Learned a lot of things in the field of working with data and files. Requires a previous Python experience (even low-level). This course is especially useful to deepen your knowledge about libraries in Python if you want to pursue a career in Data (Science/engineering). Some things are not completely explained, but it doesn't affect your global experience. Just take notes while pursuing this course and don't hesitate to ask AI (Coursera Coach or Chat GPT) to clarify vague understandings. Globally a very good course for those who want to work in the data field.
创建者 Deleted A
•Feb 6, 2022
The course was overall a very good introduction to Python with content that was easy enough for beginners to learn, but also contained challenging content for those who have experience in other languages. Overall the content also reviewed the primary libraries that are frequently used in Data Science. However, there were many issues with the IBM Cloud labs which was frustrating and disappointing. Overall I was still able to attain my primary goal for the course, which was to attaiin a working understanding of Python in Data Science applications.
创建者 Nihad S
•Aug 23, 2025
The course is mainly about teaching Python and its capabilities as theory, rather than coding, and it indeed covered different topics, from variable types, to libraries and APIs. The main issue that I did not like about the course is it is totally AI voiced, which is a bit dissatisfactory. Also, sometimes I had noticed that some points which were covered in readings, were not taught in videos, so it was confusing at times. Overall, great course to grasp fundamental knowledge about Python.
创建者 Rosina S
•Jul 18, 2022
As a newbie in python programming, the course was really informative and very practical. I did understand most especially the challenges that I was getting in the exercises on every notebook.
The only thing I did to gain more understanding of the language was to supplement my knowledge with other youtube videos so that I can fully understand Functions in python, ojects and classes and REST APIs.
All in all it was a wonderful lesson.
创建者 Douglas S
•Nov 15, 2023
In general the modules are great with nice exercises and examples in the labs. However, the week 5 (APIs) could be better explained. In general the videos are too short and go straight to some complex codes that the students are not used yet. I confess I will find another course for APIs and webscraping, once I was not able to fully understand how to put in on practice.