Learner Reviews & Feedback for Python for Data Science, AI & Development by IBM

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.

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.

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.

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).

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".

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.

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.

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.

The course content is good while the final assignment is not related to the content or even the labs and it will be quite difficult for practitioners with non-technical background

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

Failures in grammar, logic and wording.

too easy

Hi,

I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".

Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)

Course 1: approximately 9 hours to complete

Course 2: approximately 16 hours to complete

Course 3: approximately 9 hours to complete

Course 4: approximately 22 hours to complete

Course 5: approximately 14 hours to complete

Course 6: approximately 16 hours to complete

Course 7: approximately 16 hours to complete

Course 8: approximately 20 hours to complete

Course 9: approximately 47 hours to complete

This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.

(*): https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_content=10-IBM-Data-Science-US&adgroupid=70740725700&device=c&keyword=ibm%20data%20science%20professional%20certificate%20coursera&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=347453133242&hide_mobile_promo&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpWPrZDik6-Ne30To7vg20jGReHOKi4AbvstRfSbFxqA-6ZMrPn1gDAaAiMGEALw_wcB

Basically just an interactive advertisement for IBM's new product. Videos aren't very helpful as they show snippets of code without the context in which they would be applied in an actual program. Labs are okay but they use the aforementioned IBM product, and it honestly isn't that great and it isn't something someone using python to do data science would use in a professional setting. The information given about Pandas and Numpy is embarrassingly lacking so the point where doing the final lab is nearly impossible unless you already know what you're doing or you search for information elsewhere. Not why I pay money for Coursera. Wish I could have my money and time back honestly.

I'm not sure which parts of the lessons are advertisement and which parts are actual exercises that need to be completed. You are instructed in each segment (so hundreds of times) to not forget to press Shift-Enter for your instructions to be run which is annoying for something so simple. Then the lesson throws you into the deep end by telling you to get an account of gethub using gist to save your jupyter thing and you end up completely lost after clicking on too many links. I might have two accounts of gethub or none--I have no idea.

I had been taken several courses with Coursera but this data science specialization lacks good planning and clear directions to complete. I asked many times the same question. I was stuck in the last assignment of week 5 and requested help but the responses were not adequate, I contacted the teacher assistants and even the instructor and just received an email to contact Coursera services. They just ignored me; I'm not sure how many students they have but several others have the same issue with Week 5.

The third party tool is completely unreliable and it makes this course dissapointing and frustrating.

I wasted too much time trying to make it work, since it was either under maintenance or issuing bad gateway errors.

From the discussion boards, I saw that I was not the only one getting this type of errors, so it would be nice if a better tool could be used or maybe provide alternate instructions to use those Jupiter pages in Watson.

There's no way this should be considered a "Beginners" course. Exercises in labs for week 3 and 4 are very hard. The videos are very understandable but the lab excercises are too difficult. There are way too many gaps in information. The labs seem to introduce everything nice and simply, but then hit you with an exercise that is way to difficult and often uses techniques that have not been explained at all!

This course is not beginner friendly. It jumped right into the meat of things without proper explanation of terminologies, logic, and reasoning. Other than that, the videos are so hard to follow because the narrator talks so fast and the slides go by so quick. If you have expereince with Python, then this is recommended, but this is far from the "Beginner level" that this course is advertised as.

Lot's of good content. But the labs are very superficial and they just repeat what shown in the videos. The quizzes are too easy and they do not push you to actually apply what you learned. The final assignment was ridiculous. Just using Pandas to import some data, nothing more, no loops, no if statements, no analysis of the data. Continuing being quite dissatisfied with this certificate.

This course was not well designed. It needs intensive editing and rewriting.

The author emphasize the use of IBM cloud products, but the course needs to elaborate in this area if this is the desired target.

Not enough explanations were dedicated to the Python language itself. To succeed you must know some Python before you learn the course, or learn during the course from other sources.