学生对 IBM 提供的 使用 Python 进行数据分析 的评价和反馈

Low quality.

Do not recommend this course at all.

Boring teaching method.

Full of errors.

No IT support for problems.

There was 0 statistics, 0 intuition. This course looks good on paper but teaches very little of substance.

HOW IS THIS COURSE BEFORE DATA VISUALIZATION??????????!!!!!!!!!!!!!!!!!!!!!!!???????????

I have really learned many things in this course which are meaningful and helpful in real life. It is not just lines and numbers , it is exciting how you can apply these methods to find solutions in your real life problems. Combined with strong Python skills , you will enjoy more..Thank you

This was a great review of stuff math I learned in high school and college. Of course it's all easy now because it's baked into Python. We used to do it by hand and with slide rules back in the early 1970s

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

It is really a good course, simple to understand and very complete. Thank you !

Recommended course to understand the how to do data analysis using python

Well organized, good explanations, and very good labs.

Overall apt content for beginners and naive learners.

Great experience

Instead of having a lab after each topic, this course one lab per week encompassing all of the topics. Some might find that better than having smaller labs but to me the information was assimilated better when i did a lab right after the topic. That being said, you can open the lab first and follow along with/after each video. You just need to be mindful of what works best for you. Taking time to understand the code is a must and some more documentation would be helpful. I wasn't a beginner with Python and it took some time and work out what was happening at times.

Was a bit tough to keep up at the week 4 and week 5 but overall a very good course

Quizzes are too easy. No evaluation of actual code.

There is a lot of great content in this course and I believe the authors really want their students to learn the material, but the videos could be made better (make them with a real person explaining the concepts) and the labs could be more descriptive with the concepts and the authors should explain their code better. Also, there was a ton of typos, mistakes, or errors in the labs which is very annoying / frustrating. When you see these typos or mistakes it really makes you question the authors, IBM, and the material in general.

Doesn't anyone proof read the labs before they're published? Or are they just rushing to push out content?

The course included a lot of very useful information. Thank you for that! Unfortunately it is also full of mistakes/misinformation. Every time I was about to report those errors, I found out that they have been already reported in the forum. And usually reporting had happened several months ago so that left me wondering how it can be that the mistakes are still there. So far I've been participating two other Python/AI courses by IBM and they were 5 starts. For this one, unfortunately 3 stars is best I can give with all the unfixed mistakes..

Ton of errors, both minor and major, in the videos and the quizzes. For example, saying the a difference between two variables is significant because p > 0.05. I report them all and I've stopped counting.

Not professional at all.

Low technical quality of the course with lots of typos, errors and comletely mess in final assignment.

Low quality of material, bad structure, and you can get your certificate just by clicking shift+ enter

Poorly put together course - especially the labs. Frequent misspellings, incorrect links and confusing instructions. The technical problems are a greater challenge than the course material.

Not well designed at all.

explanations are lacking

Really intensive module. Be prepared to learn a lot here. You'll be diving into real stuffs that wil ask you to listen carefully and understand the matter. My advise is to take note of any points that you are not comfortable with and make additional research on google/youtube to become friendly with it.

One of the top module i've complete so far on Coursera. Full of usefull, meaningfull information and knowledge.

Great course, that builds up and ties together some earlier parts of the DS certification. It helped me to understand the process behind developing a model and then later evaluating it. Solid introduction to analysing data with Python and I look forward to applying the skills I learn here in the applied capstone project!

Really great! Tons of information complemented with exercises. To deal with the amount of material, I suggest following the labs very closely and doing a bit of research in the Python documentation avalaible online. I have to say you really hit the core of the matter in this course!

I liked so much that I solve more short test because it helps me to remember information easily and guess it allowed me to perform better. It's the first time I get 100% three times in final tests of each week.