Everything about this course is great, and there were some minor issues within labs. What I mean is that you'll still need to go to forums to find the issue you're facing like "wget command not found," somewhere along those lines, the solutions offered from the forums should've been featured in the either the videos or a part of the reading in the Reading files with Open Lab. Other than that, I can't think of any other flaws from this course.

Overall, the course is very good. Improvements could include- A primer on what Python is, what it is used for, etc. It assumes far too much of the beginner. The videos were unhelpful since they increase the total length of the course and are redundant to the labs containing the full script that is being read by the AI. I'd rather have a proper lecture, followed by a lab, where the information is explained in ways that are more approachable.

Course material in video is basic but some labs are surprisingly difficult, I have gave up on some labs in week3 and 4. I had no idea about the 'moving average' but to google it, this makes understanding the code of computing 'moving average' very difficult. So as the lab of NBA api, much love of NBA though, I had to drop it and move on with the course. I think I will come back for these labs when I have in depth knowledge of the subject.

Solid introductory course. I liked the compartmentalized approach to each of the course segments. They were manageable and easy to digest.

I found that there were some minor quirks (i.e. spelling mistakes and inconsistencies) in the short videos. I had some issues with some of the labs... it seems like some parts were editted/updated incompletely; ultimately, I was able to figure things out for myself as the labs were intuitive.

Gives a general introduction to Python. Including how functions, classes and different types of objects interact. Easy to follow if you have a elementary coding experience in other languages. Would be nice if it explains how to use and read python documentation to facilitate learning and self-suficiency. Practice exercises could also be a bit more challenging to push the student beyond replicating code they have previously seen.

Really good for what it is. But this course assumes the learner is already familiar with coding. I was. But others in my study group for the Data Analyst certifikate were not, and jumping from course 1-3 that starts from assuming the learner has never touched a computer or Excel into python programming that skips any "hello world" or basic intro is a giant leap, that I'm not sure all learners are comfortable to take.

The course allows beginners like me gain basic concept for coding in python. The discussion forums is really useful for me to interact with other students, even get help from teaching staff. However, I think the guideline for the final project can be better so that students are able to understand quickly. Anyway, I really thank for all course staff, peers to help me in this python road! Thank you very much!

Bom para aprender os básicos de python, mas um dos mdóulos, onde pedia em parte uma ferramenta da IBM cloud não funcionava, o site não deixava criar uma conta gratuíta, fazendo log out se cancelasse a compra.

Dependendo do tempo que despende, pode fazer em bem menos que as 5 semanas. Exame final é bem mais dificil que os testes de cada semana, por isso vale apena decorar e compreender muitas das funções

I am completely satisfied with the course provided by IBM in coordination with Coursera. I love to do the assignments and to answer the quizzes that will quickly assess ourselves just finishing a topic.I highly recommend this course which will cover all the essential python for the one who intends to start hos career in Data Science and in AI.Looking forward to do such great courses offered by coursera.

I have to say the content is amazing, especially the lab. However, the estimation of timing used to finish the lab is really underestimated. It takes me 4-5 more times to really go through and understand all the code in the lab, being a beginner in programming/coding. There are also 1-2 exercises where the code complex are beyond beginner level so it would be nice if there is a bit more explanation .

This course helps me to get fundamental knowledge of Python programming, APIs and web scraping. Despite of some minor errors in the content, the course is helpful for beginners. It would be better if there would be more explanation about some advanced Python programming(eg. the code "async" and "await") shown in several examples, because some learners don't have CS background and need more guidance.

This is a good start on Python. It starts very easy if you have any programming experience you will go through the courses quickly first few weeks. Even if this is the first programming course you take, it will teach you many things without you noticing it. But it gets complex at week 4. I was about to get discouraged by the labs there. However keep pushing and you will achieve your goal too!

I wasn't new to Python when I started this course so I can't comment from that perspective. This course is easy and fun for a non-beginner but I can see that going from learning about python syntax to scraping a webpage and drawing on images would seem like a leap to someone new. That being said, the jump is necessary for the rest of the specialization so I understand why it had to be made.

Course was well planned out for a beginner. I would suggest that topics on python libraries such as matplotlib and bokeh should also be included in this course. Its hard to understand the code related to these two libraries being used in the labs. Moreover, the final project should be made a bit more extensive and should require the student to discover additional material on his / her own.

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.