good course

Excellent!

Excellent

very good

Execllent

Amazing.

not easy

perfect

good

ok

The course was great but I found it a little bit hard to follow in the assignments, I used a lot of searching and googling to know how to use some of the functions or how to do some of the tasks. I spent more time on the tasks than the expected time BUT I learned a lot and I enjoyed it since I like programming!

Really Nice. But it could be a little more advanced, which would feel like a Project. It was too basic.

This may be irrelevant to this course but I need more exercises, to let me sharpen their new skill.

Challenging and informative. Some difficulty interacting with the IBM Cloud unrelated to Coursera.

A well-structured course, but there were some misleading info in the labs.

it is helpful for how to extract data form json,csv,xml

Good lessons, but I want more excercises, thanks.

I knew about ETL process in python.

The couse is good for beginners

This is a good hands-on learning course. However, a certain portion of the existing instructions/design in the final peer-reviewed assignment causes an output that, if the student is not paying attention, will lead them to submitting incorrect results during the grading process. This really needs to be remedied, though it has been addressed in the forum. Make sure to reference the thread on the Extract step to avoid this pitfall! Also, make sure to import the notebook into the lab environment if you need extra time to work through any errors/difficulties/unexpected results because you could possibly max out your monthly Watson Studio Lite usage time in one afternoon.

It delivers well on establishing the basics of webscraping and api usage. The quizzes and assignment questions could be improved by a lot as currently, they don't really do much in assessing how much one has learnt nor do they challenge you to delve deeper.

The labs are well structured though it's best if the student is left to write their own code after an example has been shown, rather than have the code or part of it written for them in which case the learning is dampened a little. For support, the solution/hint may be hidden away somewhere for the student to view if they need assistance.

The course was worthwhile, and I appreciate it. Thank you :)

The course content is good, but peer review is a bad choice. Peer review depends on everyone knowing what they are doing, but this is not always the case. It is time wasting to resubmit and wait to be graded again because of other people's fault. At least there should be a mentor who can help with the appealing process, provide feedback, or grade people who have to resubmit.

It's the most complex course I've even take at the moment in this road to Certificado profesional de IBM Data Engineering. The previous Python for Data Science AI & Development give the basic tools for doing it but the level of complexity, the unclearity to understand what we have to do and the excesive quantity of optional labs do it very difficult to understand.

This course could be much better. The lab work does help one to grow in their ability but there are mistakes throughout the labs giving the sense of a lack of care going into its design including a lack of pedagogical thought and skill. I am generally concerned that the 'rating' system of ed tech is increasing the ability of marketing to hide low quality.

There were points of confusion in the hands-on exercises. A week of Panadas and perhaps a little deeper dive into Beautiful Soup would go a long way to make this a stellar course.