The content was good, but as with most online programming courses, there simply are not enough coding exercises to effectively retain the knowledge long term.

There were some errors in the notebook code and some of the video quizes asked questions about things that hadn't been covered yet.

Final exam poorly designed and written. Frustrating experience trying to find solutions. Needs a rethink and more structure.

the questions given in the final project are not covered by the course materials

The course is super frustrating, the robot voice for the videos makes it so difficult to digest the information, the cadence and focus on certain words is completely wrong, so it makes it so hard to understand, especially when introducing new terms. Given that a lot of the information is presented on slides its really tricky to read at your own pace with the correct intonations and also see the code on the video. It seems really lazy to not have a person with subject knowledge read the video material in a much more engaging way (as with all other Coursera courses I've tried) - this would make the material much easier to engage with and less like I've just installed a text to voice reader on a wikipedia page.

I also think some more real life application based would make it much easier to engage with the material - when I've looked at other courses (e.g. Khan academy, codeacademy, they at least explain 'for loops can be applied for example in XXX'. The labs are good, but the videos have to be some of the least engaging videos on programming that I have ever come across!!

Also, Also, a lot of terms are introduced without any explanation as to their function. In the videos sometimes terms are just introduced on the screen e.g. '_init_ ' but with no explanation whatsoever as to what this means or when it's used. This is meant to be a beginner course and provide knowledge to apply in a workplace setting going forward, but I find myself constantly googling to get background information on Python code. As an example, I messaged my friend (who is teaches python in a university) who gave a brief explanation to 'init: "Short for initialise. When you create an object of any type, you either create a real one or a default one. So for the circle example, a default circle could be the unit circle, but you (as a programmer) may want a 5 inch circle so you would use the class constructor to initialise / override the default values" .

This kind of simple background explanations would go a long way to actually teaching people how to understand what the code is doing, and the background of it and why you use it, so that you are actually more capable of applying this in a future setting. It also helps make the course a lot more human, rather than trying to teach it in a way where you can only remember the code but not actually understand what any of it means or does!

I'm really disappointed with this course, I hope the other IBM python courses are better!!

It's funny how the last thing we learned about is beautiful soup, because that's exactly how I would describe the course , except for the beautiful part. It's ugly.

First of all the course lacks organization. You learn how to import CSVs in the begining of week four, and how to import JSON files at the end of week 5. Wouldnt it make more sense if the two topics were covered together? and no I did not need to know what a JSON file is before learning how to import it. It's enough to teach me how its structured.

And this philosophy is carried all over the course. It seems like IBM is confusing the forest for the trees. The module working with webscrapping had two vidoes explaining the communication between client and resource, and two other videos on web scrapping itself. IBM, listen to me, teach me practical skills, I can use beatuful soup without understanding how it works under the hood. Spend that time on things that actually matters.

Okay fine, the course is a mess, but did I learn something useful? yes, but that's thanks to the many tutorials I read/watched on other websites. This course jumps from covering the absolute basics to flashing an advanced concepts and moving on. For example, we learned how to create a simple dataframes, but grouping and aggregation, the stuff that actually matters, was only flashed on the screen for 5 seconds in a video on APIs. How am I supposed to do analysis without learning about aggregation? Well thanks to youtube I can. If this course is useful for anything its to point you to the right direction. Self study is essential.

The lab sessions are borderline useless, 90% of the exercises are super basic and were covered in the lectures, but are these any example datasets to work on? is there a multi step analysis to complete? are there any problems that go beyond creating a smile 1 line of code? not really. That's up to you to do on your own.

I'm comparing this course with the Google Analytics module on R, the difference is night and day. This is simply a low effort attempt. I expected better.

The first two modules where really good. very beginner friendly, but everything after that was way to advanced. I spend a lot of time each day on Coursera so i can learn and practice, but i was stuck on everything after module 2 for almost two weeks and it was so discouraging because i though i was the problem and just wasn't smart enough to learn Python. After looking at the discussion forum though, i realized i wasn't the only one confused and lost from how advanced everything got so quick. this defiantly needs to be looked into and made easier to understand and we need to be taught how to build and form the data correctly. so many new words and codes where introduced too soon when we didn't even understand what each part meant individually. Also, the labs need some work with the spelling and solutions. There where to many times where incorrect spelling in the solutions led me to errors and i would end up giving up on trying to figure out what should be there. All in All it could have been better. I watch Bro Code on youtube and he teaches a lot of the material taught in this course but simple and beginner friendly so it is possible to simplify this course.

It wasn't a bad course, but I have some reservations. 1) I'm not sure about the beginner level. The beginning is nice and easy, but in the labs, there are some things that aren't explained at all and are just... there. An absolute beginner has no chance of knowing the purpose of the code, etc. 2) Someone should consider a revision because some things just don't work outside the Jupyter Notebook. Maybe this isn't a problem for many people, but when learning, I prefer to have the materials on my PC, and this wasn't entirely possible without the help of ChatGPT. 3) I wasn't able to download the cheat sheets as PDF, even though it was written that you can do it. I tried other browsers, but I just couldn't. 4) There were loads of typos and inconsistencies. I would expect more thorough work, especially when it's not just a course you have to pay for, but an IBM course.

This was the most disappointing of all the courses I've taken on Coursera so far. The learning curve has not been well-defined, it's riddled with errors and forum posts are met with standard replies (if at all) without ever correcting any errors or updating the course material.

Forum posts dating back to months ago can be found with the same errors that still exist today.

Rarely do the people replying to our complaints ever admit to the errors and in some cases, posts go unnoticed for over two weeks.

Thankfully, this wasn't my first exposure to Python. I shudder to think what someone who isn't well-versed with debugging or online documentation would go through.

I'm sorry I've had to use such harsh criticism to make my voice heard, but please, fix this course.

No doubt your burden is a heavy one and you do a great job in many ways, but this one just fell short.

This course was a mess compared to the others I've taken so far in the Data Analyst Certificate. Yes, the subject matter was much more difficult, but even so, I feel it was taught much more poorly. There were many typos and instances of unnatural language (no one says "let us" - use "let's"). Worst of all, advanced code was frequently introduced with virtually no explanation or context. Some of it was not important and was just there to help illustrate other concepts, but some of it was necessary to learn and used in the labs. The class needs to explain which is which. I constantly felt myself asking "why" and getting no answer. On a more positive note, I did really like how the labs rehashed everything in the videos, so I could just take notes there at a more natural pace instead of pausing the video dozens of times to write.

As the name says, "Python For Data Science and AI", but to be honest, it covers very little learning materials related to data science and even lesser for AI. Every week it makes you sign up for IBM Watson Studio. The worst part is in the final assignment, you are not judged for your ability to write python codes, it judges you on sharing your IBM Watson studio link. The level of the final assignment was quite low as it should have been.

I don't understand why can't we do the same assignment somewhere else. How this low-level assignment be a part of a specialization course? And the slides demonstrating the procedures of IBM Watson Studio is outdated. This must be improved.

The course is a brief whizz through Python and could be good on its own as a refresher for those who already know the basics of Python, however it is the final assessment that spoils the course - this assessment was probably written by different people who did not see the course itself. It does not test your Python skills, but rather your ability to set up IBM Watson Studio and IBM Cloud Object Storage, which is a pretty fiddly service for the uninitiated. Did I learn anything useful from this assessment? Probably not. There are far better Python courses out there, e.g. check out the one from the Higher School of Economics.

The Coursera's curse hits again. I can't recall an entire specialization in which, at some point, I didn't feel completely lost. In this instance it took 4 courses. I don't know what happened in the 4th week but personally I would have spread the content into 2-3 more weeks, with way more practical exercises and examples.

The final project more or less comes out of nowhere, there is definetely not enough material to face the 4th question (unless you had previous experience with Python).

The course is very simple and short. The "data science" content was importing pandas and casting lists to dataframes, and there certainly was no AI content. It seemed like the instructor just wanted to get making the course over with, especially the later quizzes - the week 5 graded quiz only had 4 questions. The final exam was 25 questions and only 1 covered week 5.

There's no reason to take this course unless it's for a specialization/professional certificate.

This course is a good base, but is really in need of an overhaul. The fundamental pieces are there, but the material is riddled with typos, expectations of reading tutorials that don't exist anymore, and incomplete instructions that leave you in the dark. I wish they would not skip over concepts as they are introduced, but instead give even a short blurb about what it is so that we get used to seeing the more complicated code that is "skipped over".

Not for beginners. Difficulty ramps up extremely quickly, and instructors offer little to no support. I requested help on lab exercises more than once and received responses like "just use logic." I find it hard to believe that anyone without a programming background can succeed in this course. Sure, they can pass--the exams and quizzes are not challenging, but the lab exercises are far too complex given the content of the instructional videos.

I'll start with saying that whoever designed this course knows nothing about how to educate people. Have you tried going though it? The video lectures are read by a voice that sounds like a robot. Also, majority of things taught here have zero context on how we can use them to solve actual data problems. The final exam is a joke, not because the course is good, but because it's objectively speaking easy. Overall, an educational disaster.

Are there other training videos or literature on Python? The videos are very hard to follow and the narrator speaks too quickly especially for a novice. The videos are badly edited and this make the learning experience even harder.

More working examples to keep practising would be more helpful. The Labs are also unreliable and are often inaccessible. I am disappointed so far.

The first three corses in this professional certificate were very good and was taking me step by step. But in this course, everything is just running and jumping steps. The videos, quizzes, and the first part of labs are in a level, and the final assesment in the end of each lab is in a whole other level especiall in week 3 and 4.

I guess this course is currently being updated and transitioned to a new course, but the labs include material that is never covered in the videos, there is a steep increase in difficulty, and the course is NOT a "beginner-friendly, no experience required" introduction to Python as advertised. This course needs a major overhaul.

It has some errors between the narrator and what's shown on the course.

I had to rewatch the videos a few times to understand that what was being shown wasn't the same thing the narrator was explaining.

Also, the submission of the assignment wasn't working and nobody from Coursera would step in to answer/fix the issue.

Some things were repeated. Many details were omitted. Did not go far enough into OOP. The learning for XML was under all criticism, did not go through it well at all. Some pandas functions were used without explaining what they do (groupby and agg for example).

I was stuck in Week 4 and 5 as the exercises are far different from what I (and I believe other students as well) have been taught from the videos and labs. I do think you need to restructure the course to be easily understandable for all of students.

Not a beginner's course. Because I learnt some python I understood the concepts which I know but "objects and classes" concepts are not at all clear. I wanted IBM to improve and make it beginner's course.

Many of the labs did not work or had errors. The solution each time was to "create a new account with a NEW mail ID".... That is a terrible solution and does not suffice for ideal learning.