The final exam had nothing to do with the course at all. Very poorly thought out.

Decent, but you barely get any experience yourself

very basic .could be little advanced

In general, the material is well presented in this course. If you already know Python programming, probably most notions and examples will seem trivial. The labs are really important to gain a deep understanding of the course material. But you won't get to actually write your own code with a very few exceptions (e.g. the urn problem). The multiple choice graded questions most of the time aren't multiple, aren't randomized (thing peculiar for instructors to omit, in an allegedly data science course), are trivial and don't get deep on the programming aspect. The instructors are almost absent with minimal presence in the forums & discussions. Last week's graded assignment is about compiling an already existing code in the jupyter notebook and you will waste a considerable amount of time trying to submit your work via IBM's cloud rather than actually working on the code itself or on understanding the underlying notions and concepts. In summary, this course certainly has a potential and can be improved on various levels (instructors availability, problem solving, etc.), but if you already know programming I believe this course will be of little to no use for you, except if you want to spend some time and money during lockdowns. If you do not, you will probably get a grasp of the basics of Python programming but, in any case, do not expect to improve your problem solving skills. Nevertheless, if you combine this course with a personal involvement in solving programming problems via Python it will could be beneficial, however I am not sure if it's worth the money.

The course is not well structured for its intent. They condensed so many arguments that at the end I have the impression not being able to do at least half of the arguments I studied. The big problem is the gap between the code showed in videos and the one proposed inside LAB. Starting from week 2 we are going to face so complex code that you waist a lot of tyme trying at least to understand it. Being a paying subscriber I expected much more. Just for curiosity I found out on internet the DataCamp site and I ended to subscribe also their courses. I want IBM certification, but I'll use DataCamp Courses to better understand the arguments faced on Coursera. My suggestion for Coursera and for the ones created this course is to review entirely its structure and provide better examples and use of code inside lab notebooks. Anybody is able to click the "run" button to see the output the code, writing code is a different thing and it requires going throug steps and not jups frome too easy to impossible.

Let's be honest, no one without any experience of programming is going to be an expert by the end of this course. I have learned a lot, yes, but I am far to be a Python programmer even less specialized in Data Science at the end of this. The lessons are very basics with a consistent frustrating exercise at the end of each and every lesson: for some reason, the author assumes that you already know how to program with Python, so the exercise is about something which never ever was even mentioned during the lesson. Some lab exercises are largely outdated as mentioned in one of them: "This lab describes the current version of Language Translator, 2018-05-01" in March 2021... Now, the final assignment was actually the most interesting part of the whole course as data science was actually involved with interesting data even though there was still that frustrating question about something never spoken during the course: finding a value greater than the other in a column.

Some of the code doesn't work, is wrong and outdated! so spent too long trying to unpick why e.g. !wget

The labs are not good for practicing its often a repeat of the material in the video - you need to build some exercises into this to help students write the code than be spoonfed in places.

Some of the code e.g. where you're importing a library. doesnt have a comment - this is bad practice, so without googling it no idea what it's doing.

The quizz embedding in the video is just annoying especially that they are the same questions at the end.

Can no longer sign up for free to IBM cloud account and the instuctions from 2020 when this was possible. you now need a credit card to do this where you get a limited time on the trial. UPDATE YOUR COURSE!! Do not use this as an oppertunity to sell me IBM products i already pay for this course - have discounts or something for paying students!

Waste of time and energy!

In my opinion, this course goes all over the place. The video lessons are thrown at you too fast, it's hard to grasp anything really, It's not well structured at all..

I was fortunate enough to have some basic Python knowledge before this, so I could get a thing or two.

The final assignment should be greatly rethought, even scrapped for something that actually lets people put their lessons to good use. The last two weeks are spent on methods and some basic data analysis functions, which is good and all of a sudden we are tasked with making faks album covers...

A good improvement would be to create an assignment which lets people practice a lot of things shown in the course, not copy pasting some code and rewriting a function...

Disappointed. I started off enjoying this course and was taking the time to fully understand all the concepts of Python. By the second week, JupyterLab was not working and for 3 days I was trying to connect to it, to do my labs. Although I was continuing on the course work, not being able to do the labs was keeping me behind. Others in the discussion forum were concerned about the same issue but I do feel at this stage that someone should be able to notify the group of these issues instead of people wasting time trying to log onto something that has a technical problem. I eventually unsubscribed from my certification as this was not an efficient way for me to study, and was using up too much wasted time!

Not a gradual explanation of the concepts or ideas, around week 4 picks up really fast, compared to the past weeks. Week 5 is too much too soon. Also, at some points the material seems a bit rushed., with grammatical, syntactial or even basic spelling mistakes, such as "songe" instead of "song", or "sting" instead of "string". There also isn't from what I recall any guide on how to donwload and run the given code on one's own computer through for example visual studio code. There also isn't any guide on how to use visual code or any other similar program. Most of the time, the information given is just copy pasted from online documentation, for example for "beautiful soup".

I would not recommend this course (and the previous ones too) for beginners. I passed it having some experience in programming and basic analytics, so it was not hard, but it was absolutely boring, had a lot of excessive information and had not enough explanation within videos. For the sake of justice, reading sections contain some additional info but in general not very interesting. Highly recommend other courses, for example from Udemy. And the most important - try to learn python first of all on practice, there are a lot of great platforms such as Codewars, Hackerrank etc. It would give you much better understanding how to write code and what it all means.

I really did't like it, it was really in sometime complicate, to undestand and to follow, there is something missing in the course, theory that the course do show it and has to be better explain. I suggest to add more dynamic excecises like, go and extract this information from this site and pull it into this place, once you have it, create another thing.... and at the end you will see this and this and this.... I really enjoy the IBM products and courses.. and this course is not all bad... just need some corrections to make it more attractive to people who wants to change carreer to this fantastic world of Data Engineering.

I found this course to be extremely un-engaging and mundane, and I really wouldn't call it beginner friendly as it jumps from subject to subject and doesn't provide enough context for a deeper understanding on the subjects it's actually teaching. I just wish the whole course wasn't AI generated as I just struggled to feel any engagement in what I was learning. If you're looking to learn Python from 0 I'd highly recommend starting with something like brilliant.org, I found it a lot more engaging and actually retained the information being taught. Stay clear if you're starting all the way from 0

Though I do feel like I learned some things from this course, I was not very happy with the way the material was presented. The first half of the labs were great, but the second half was way beyond what was being taught in this course and difficult to follow. I ended up skipping those sections and still did well on the quizzes. I think those portions need to be removed. There were also a few quizzes with answer errors. It took several times of answering the same thing for it to accept it as the correct answer. If I had it to do over again, I would learn Python somewhere else.

the course was extremely fast paced and skipped over a lot of basics. It felt like there was a lot of information thrown at you and not a lot of practice or review for it to settle in your brain. I typically enjoy fast- paced courses and have a little background when it comes to programing, but I still could not figure out a lot of what was going on. Also, in most of the classes we got an explanation of how to use the basics but then were faced with a code that parts of it were not explained, and therefore we could never do all that we were taught by ourselves.

I found many videos/tutorials to be very dry and difficult to relate to/comprehend. I spent a substantial amount of time seeking out other tutorials and videos that could explain things differently and give me more practice. I also found that the lab exercises went from very basic to very complicated, with little help to bridge the gap. There was also at least one lab that did not function properly, so I skipped it. I struggled to do the portions where the learner is to write the code themselves. It was very frustrating.

Maybe it's a good introductory course for Python, however, I got an impression that the authors gave up three quarters into the course. The labs become more of a reading material rather than a place where you can practice a hands-on approach. The final assessment - omg, I fail to see any relevance between the course material and what is expected in the final assignment! The only lesson I have learnt from it is that I shouldn't trust online courses to learn a subject.

I would not recommend this course to other people.

This is described as a beginner's course in Python. In the labs, the examples you are given are basic and easy-to-follow examples that DO make sense. However, then, in the activities, they give you wildly more difficult tasks are nearly impossible to create on your own without looking at the solution while writing the activity's code.

If you would like to have a basic course on Python that will actually train you on how to use it and be more of a staggering difficultly level, I would recommend NOT taking this course.

"I enrolled in Python for Data Science, AI & Development course with high hopes, but I was thoroughly disappointed. The content was poorly organized, making it hard to follow. The lectures were dry. The assignments were vague and didn't align well with the course material. Overall, I didn't gain much practical knowledge or skills from this course. I wouldn't recommend it to anyone serious about learning Python."

I'm not sure I'm supposed to be learning from the Labs. The videos don't exactly show you how to perform the tasks and the practice Labs jump the explanations for several fundamental steps. Frustrating to say the least.

I was expecting more about Data Science, as mostly was a quick introduction to Python. It took one afternoon to do 5 "weeks" of work. Perhaps too easy to be connected with IBM.

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Unnecessarily long. Each lesson you watch a video, then read the same thing, and then read the same thing in the lab. It does teach you Python though

Bluff..AI *is not covered and the whole course material is for only python basics. Need a revamp which will include AI-based materials

My goodness this was wrought with errors. There were a lot of incomplete concepts and poor examples.