Course is great. Need to spend more time to learn Python concepts. Lab exercises are great concepts to be learnt. Few lab exercises not working in proper manner. File concepts should be tested before students can work. Few import libraries are not working properly. Lots of concepts introduced though, needs time for students to progress. I guess the time frames scheduled are NOT ENOUGH!!

I did not enjoy the final assignment. I ended up having to use a notebook outside of Watson studio. Moreover, I found the array dot function examples confusing because each dic was the opposite and therefore hard to distinguish how the math was being peformed (e.g. a=[1,2][2,1] b=[0,1][1,0]

I spent hours on this section and ended up finding out exactly how the funciton works on youtube.

The course was very well structured. The only thing that i did not like was the exam. It looked like it was prepared on a run just to have something. Otherwise very highly recommend the course. It starts with some basics and also pandas and numpy. Also some basic Object Oriented Programming.

You have to go throw the notebooks slowly if you really want to learn the material well.

Although I already was familiar with Python but still I was able to learn something new from this course for example how to use Pandas and Numpy and what problem each of them are trying to help you solve. Still a 4-star from my side because I think the course could've been a little confusing for someone not familiar with Python but overall it was good learning experience. Thanks.

Some difficulties faced with the integration with the IBM Watson platform. Without proper technical support and some more extended technical training you may get lost as this is a quite a large multilayer environment. Maybe a dedicated session needs to be devoted to the IBM Watson platform foundation. Overall a very good course providing a solid foundation on Python. Thank you.

This is such an amazing course and must do for IBM Data Science or Full Stack Devloper certficate.

The only reason I am giving one star to it is because it Starts from the very beginning and completes to very advanced level python in just one course which is quite not good for absolute beginners.

So if you are going to start it, make sure you know python at least at basic level.

Very good course, the fundamentals are approached in a very easy way and understandable, though I think the exercises could be quite harder to train programming basic skills, because if the course does not do that, then just the syntax is explained without the development of applications skills that are far more important than anything else in a programing language course.

I loved this course. The course covers all major topics from Python and gives a good walkthrough on the concepts required further in Data Science journey. But would suggest the course to be a bit elaborative in terms of labs and activities, as for 1st time Python learners this could be very quick. This course is best when you already have some basic knowledge of Python.

Very good with loads of hands on examples. Only thing was that sometimes the cell calculations would be messed up when testing different codes, and then I had to reset kernel and go to top to reload necessary packs and run the required code lines again. I am sure there is a good way to handle this. That would have been great to get explained in the first hands on lab.

the material of the course is awesome, the practices are sufficient and helPful. along with the videos are very clear what to pay attention to. However, the instructions for practices are sometimes confusing. The amount of different applications used were overwhelming. it would be better if work can be done in just one app instead of making many different accounts.

Very basic, assumes no prior programming, which is a relief for most intro courses. Would have liked a bit of what we use some of this for; the course just kinda "starts" and goes along. Lots of typos, too. Didn't like the end project. Confusing directions, and didn't really use the functions we learned about in the course. Lots of google and guesswork on my part.

This is great course with a lot of good information. I will say that it does go a bit beyond the beginner level and moves a little quick so you may need to rewatch the videos sometimes. I took prior python courses at the beginner level, so I was able to manage; however, without experience, I recommend using YouTube videos to fill in parts they kind of skim over.

Many thanks to the course designers.

Text Analysis exercise has a very steep learning curve. Need to segment. Start with simple code, then provide the equivalent "superior" code.

Same issue with Raptors fan club exercise.

Had issues with wget installation. IBM cloud feature code failed. Had to use new mail address.

It took me double the time to complete the course.

Some part in the labs wasn't functional due to missing installation of libraries. Also in some places the code didn't run as excepted only after manipulation debugging and WA. I think that once in a while the course should run in a regression test to catch this errors.

I believe this is due to libraries dependencies etc.

Over all, I enjoyed the course very much.

It is an amazing course where everything is taught from the basic. One can follow the lectures very easily and can apply it. Video lessons are good and test questions could be little more better, it was way simple. There will be difficulty in searching the assignment data for students but it is fine, we can look out for it. Overall, it was a good experience.

Overall the course was decent. But I strongly felt that at certain points, it went at a very accelerated pace with little explanation. I Hhd to repeat and watch some parts over and over again to understand the concepts. My only suggestion is to reduce the speed of the program for beginners to understand better. Otherwise, it is a good and complete course!

Great tool to manage and understand how to work with Pandas and the basics of Python programming. Honestly, it is worth to do the curs even if you have no idea about Python. There are step by step manuals about how to program this stuff. It is far away from difficult! Though a tip is to try to run this on your computer and keep some examples. Great Job!!

It was good for the python basics. Eventhough I knew most of it, it was nice to go through and see where I still missed some things. But the part with the web-scraping and API´s was too less to really gain knwoledge. It would be better to make a own course only for that and maybe add visualisation libraries like atplotlib and seaborn into this course.

I learned a lot from this course but am trying to experiment with python on my computer as this moves forward but often encounter many syntax errors due to not learning it. I think it would be beneficial to others if syntax is explained first and some theory instead of just diving in but just my opinion as my learning style is different from others.

This is a well-organized course that requires a certain prior level of programming knowledge, as well as commitment to studying its lessons. The course prepares the way very well for what later should constitute the following more specific courses. Again, it is a course that requires commitment and study, but you learn a lot as you dedicate yourself.

Lab is quite glitchy as it showed errors for the correct codes too. This does not help as it adds to the confusion and also makes you lose interest due to uncertainty and frustration. However, the culmination of videos and reading are great. Despite the glitches, the labs do offer oppotunities to practice your programming skills which is wonderful.

A good course for the time allocated. Touched and showed the basic of modules interesting for Data Analytics and Data Science.

Missing start is due to there were a few steep steps in hands-on lab but I think it is needed if the course would not be too long and extensive.

Enought to get the basic and knowledge to take other course or learn by doing

Highly recommended for any beginner who wants to get into data science. The transition between beginner and intermediate is so student friendly.

My only suggestion would be a little reduction in the speed with which instructor take class(in future course lectures), its slightly difficult to take notes. But we can we view it back, so not a big deal

The materials in this course are very useful. The techniques in the exercises are relevant to real-world problems. The final project has some bugs that should be addressed; namely, the lab environment does not support the plotting method used in the template, and the template is not readily available but must be found in the Discussion forum.

Good Course, covered ONLY the basics of Python. I did not like the tasks because they were very easy to solve, while the actual cases, problems will be much different and difficult than the one covered in the course. However, the course was just the starting point. It was good, fun, educative. I recommend this course as a start in Python.