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.

I really enjoyed this course. Few things to suggest:

- Go over Statistics in more detail. Had I not studied Statistics in university, I may have found this topic confusing.

- Felt like I could have learned more if the labs were not filled-out halfway

- Too many multiple choice questions in the quiz and final. These should be more interactive with lines of code we would type insetad of clicking a bullet.

- The math covered in this course was very high level. I.e., Chi-square and linear regression require more hands-on practive in order to grasp.

Loved the labs. Hated the Videos. The amount of information that is thrown at you in a 1 min video is very unsettling as it makes you think you haven't understood a word of what they say and then the labs immediately clear everything up and then you feel like the smartest person alive. It's an uphill battle at times but the end result is pretty helpful regardless of the reason you're perusing the course.

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..

Really didn't go into too much depth or gove more examples or breaking down any of the functions used. It really is couse for those that already know what they're doing. And top of that you hae to wait for a peer review to complete the couse. Really didn't feel like I learned too much.

I can't believe this course has an average of 4.5 stars. I think they're fake reviews.

They state that no previous knowledge is needed and yet the topics are complex and not explained during the course. They give you information without any introduction on them, giving for granted that you know that information.

There's a lab to exercise that is full of bugs.

If you want to learn Data Analysis with Python and you don't have any previous knowledge of Python, Statistics and Econometrics, stay away from this course.

Probably if you have a firm knowledge of the above subjects it can be useful.

I think people rated it with high score, because it's easy to get the certificate, not because is useful in terms of learning the subject.

explanations are lacking

Overall I learned a lot from this course. However there were too many small disconnects in the course, especially between the video voice-over and the slide material. It was like the video presentations were not sufficiently quality checked to make sure her spoken words matched the written words. In weeks 4 & 5 there were a couple of times when she named one function and the slide showed a different one. When one is still low on the learning curve it is very important that the consistency of the material is solid. When there are needless ambiguities in the material, valuable learning time is lost trying to figure out something that is more "container" than "contents". This stalls the learning process and can create a lack of confidence in the material. Good but it could have been better.

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.

The courses from IBM on Data Analysis, Visualization, Machine Learning are great. I am in an online M.S. program, and the material from IBM is lightyears ahead of my university material.

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

Great course. I had fun having a kick start in the field of data in machine learning. I understood the concepts related to how to improve the model.

Thank you

Great Course. Amazing Work By the team. Concepts explained clearly, followed by the week end quiz to revise. The Labs Do a great work in helping out

helps me a lot! FYI I was new to data science and programming language but this course helps me to understand business analysis with Python!

Covers a lot of ground but the Python Labs are great at bringing everything together.