Avis et commentaires pour d'étudiants pour Analyse des données avec Python par IBM

Very low quality of the course. The structure of the course is illogical. Also it takes too little effort to accomplish the course. In the beginning of th course labs contain all the code so a pupil doesn't have to do his/her best to solve tasks. I can just constantly press ctrl+enter and get my certificates. It is not what I expected from the course. Also quizes never contain coding practice, so to accomplish I just need to show the understanding of the basic aspects of the topic, not the coding skills. The, at the end of the course (after I have lost all the motivation during the first weeks you give us difficult function, including custom functions, never explaining them at all). Have a huge doubt about buying the subscribe for the next month.

So many mistakes in videos and labs, including spelling errors, misnaming functions and code that causes errors.

These have been listed extensively in the course discussion forums, with some complaints from over 6 months ago, and have not been addressed

Many typos and other errors. My favorite was the video where they said "150 - 50 = 50"

I am working through the IBM Data Science Certificate courses (in order) and this is easily the best one I have taken so far. Once again, the labs provide a variety of hands-on exercises that help to cement the topics introduced in the lectures (which, to be fair, are very fast-paced). Everything taught is practical and relevant. One request would be to fix the pacing of the videos and lecture quizzes, which often appear to test students' comprehension mere seconds after the topic was discussed! I did also notice a few errors in the labs, but they did not stop me from learning the material. Overall, great course.

Thoroughly appreciate the effort to put this course together, however there are several problems (I think this is the worst quality course I've seen on Coursera so far .. or maybe all other ones have just been great!) -- a) the instructional videos contain many errors in both code syntax, and, worse, in logic; b) questions on Forums take a long time to be answered, and staff member who responds to most of them appears to be a bot/only provides vague general info; c) course material has ups and downs, for example Inferential Statistics are blazed through within 15-20 minutes, and there is very little discussion of, say, how to identify the distribution of your data, how to decide on parametric/non-parametric tests and so on.

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.

Honestly, I'm not sure why this course has such a high rating. I feel like it can't possibly be a reflection of what actual students felt about the course. Reading the other reviews, it's clear some of the issues people had with the course were not the course-designers fault. But, there were some tissues that are simply inexcusable. For example, typos in the lectures (especially towards the final week) show little to no proofreading was done. A lot of the labs involved "Warnings" that the instructors didn't explain to students (and so obviously some students got confused by them, even though they were inconsequential). And the final peer-graded assignment was a complete mess. The first few questions are numbered Question 1, Question 2, Question 3, etc. But the last 4-5 questions are not numbered making it very annoying to upload screenshots for each question. The directions in the assignment were simply wrong. For example, one of the questions didn't even have a prompt, just an empty text box. Someone asked about it in the "Discussions" and a staff member replied but it was never fixed in the assignment.

Trying to put the typos and logistical confusion aside, the course material was oddly organized and students were never really given an explanation as to why the concepts taught were being taught in this way. My least enjoyed course of the whole specialization.

Too many new functions with no option to practice. New and new and new library each week, in the end it's a total mess in the head.

This course should contains real excersises, lots of, just pass the test doesn't mean that you become familiar with the material or remember smth.

This needs to go much more in depth on the options for analysis, and provide more examples.

In addition, the labs and final exams were not fully completed/corrected/reviewed, so there were many erroneous issues, including assumptions made that was not clear to us students.

i was following nicely until week 4 but halfway there it got really difficult. To a point in week 5 when all i could do was copying code and adjusting it. I have no idea what i was doing, i totally lost the bigger picture. I'm sure i could never replicate any of it outside the course or explain what i learned.

I felt the course isn't designed well as it takes you little fast than expected and doesn't explain all the terms! May be one has to be very good at math or revise all the topics before taking this course.

I didn't like it at all

although its the most important course in the whole specialization but it's really bad i didn't understand a thing

Very serious, professional, empowering course. Clear straightforward detailed explanations. A good deal of practice.

Avoid this class. Unfortunately, the labs have been broken for several weeks and there has been no helpful response from anyone other than stating that the labs are being migrated to a new platform. The migration has been woefully unsuccessful and the labs continue to be unavailable or non-responsive. I am very disappointed in this class with several weeks wasted trying get through the course.

A seriouse deal of statistical modelling taught with a perfect content. I really appricate the effort put in order to not being "hard-to-understand", but still finding the way to teach complex statistics. You will have a very good useful knowledge of statistical modelling without getting lost through too many greek symbols and long explanations.

best course for beginners

Decent introduction to basic concepts of data analysis. However, the 'labs' and quizzes feel insufficient to practice the theoretical aspects. Further on the downside, the quality of the material in this course is quite poor. Even worse, several months after learners mention errors in the discussion forums (and partly get an instructor response), the mistakes remain in the material.

I'm sure a number of people put loads of time into this, so, thank you!

This must be the absolute worst online course I've ever come across ever! First of all, there are so many typos and mistakes in the course material, which is totally unacceptable! Then, there is no logical continuity in the subjects presented. The course is supposed to be intended for beginners, however, there is no background information or reasoning behind what is presented. Many times, one may only copy and paste python commands without knowing why or what it means at all! Unfortunately, This course is a disaster, and hence, NOT RECOMMENDED AT ALL!

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

Thank you so much! - Oana

None

The techniques, methodologies, and tools presented here are essential parts of the data analysts tool box. The coverage was, in general, well done. I am glad I took this class, and look forward to the next.

That said, there were problems:

1) The meta parameter, Alfa (or is is Alpha) is never explained, except that it helps. To be useful, the student needs to know a bit more. Also, the spelling should be consistent between the training texts and the lab.

2) The lab needs maintenance to keep up with changes in the Python packages. I received warnings about using deprecated functions and values.

3) The text needs grammar/spelling checking, for example, the end of the course exam is labeled "Quizz"

Does an excellent job in providing the Python commands needed to do data analysis, along with some descriptions of what the steps actually involve. Has quite a few typos and minor issues -- looks a little sloppy.

Too many mistakes in the lectures and the main lab. Confusing for new learners when the math is wrong or the python syntax is wrong. Anyone who rates this above 3 stars you are simply not paying attention to the myriad of mistakes.