Kursteilnehmer-Bewertung und -Feedback für Applied Data Science Capstone von IBM

good

Good

nice

good

Good

AAA

<3

f

9

This is the final course in the IBM Data Science Certificate and it is primarily focused around a project of your choosing. First, you learn how to scrape data and use the Foursquare API, which is quite helpful as these skills are generally transferrable. Then you'll need to come up with an idea that is loosely related to location data in some way. You'll have several weeks to implement your idea and write a report and a blog post/presentation. The final project is a lot of work.

In my opinion, the grading system could be better. You rely on peer reviews to pass the course, but only one peer looks at your work. Multiple sets of eyes would be fairer and hopefully generate more feedback. The discussion forum aspect could also be improved to promote collaboration and not simply requests to "please review my submission".

All in all, a decent guided Capstone course. Be prepared to do a lot of work on your own as there is not a lot of structure or hand-holding. I am very proud to have completed a formal project/report that demonstrates how much I learned over the course of the IBM Data Science Certificate.

This course is excellent at teaching all the data science and machine learning skills from a practitioner's perspective. I would strongly recommend it to aspiring data science professionals. Other positives include free introduction to the IBM cloud platform.

Room for improvement include:

1. Improvement to reliability/availability of IBM Developer Skills Network (which was done towards the end of my course) or give it a miss (using IBM cloud platform instead) completely.

2. Assignments should be graded by instructors or through standardised testing. The current peer-graded system seems to be hit and miss. It is not ideal especially for such a long course.

There were quite a number of tools/apis in the course material that were no longer working, meaning they need to be updated and shows the course material has not been touched in quite some time. For absolute beginners this is problematic as they are not unsure where to search for solutions, and asking in the Discussion Forums does not always return an answer. Aside from that, I found the Capstone Project to indeed be challenging for the level of skills we have obtained from the course, but also figured it forces learners to really search and source for solutions similar to how the real world would force you to do so.

This course has been a real challenge for me. I've spent many more hours than planned to complete assignments of week1 and 2. I don't know if that is because of the topic I chose or because of the problems I had with Watson.

In the middle of the course, Watson stopped working ("monthly capacity reached"?). After asking for help in the forum, I didn't get any until 10 days later (and, by the way, what I was expecting). I somehow managed to install Juyputerlab as an alternative solution, but to do it properly and being able to publish some data into Github added more complexity to the challenge.

I had higher hopes for this....The videos are excellent, the labs are pretty good. The problem with the labs is they will just dump the code in and expect you to know what it all means. I spent a lot of time googling what the code means for when I apply my own analysis. Begs the question of the value.

Lastly, the capstone was more of the same. A lot of digging on my part and not much help from the videos/labs. Also, many of the labs are outdated and you have to search the forums to find out something was deprecated and to use a new function. JUST UPDATE THE LAB!

The course is good. It makes you think on all the knowledge acquired during all other 8 courses and make you put in practice.

The only drawback in my opinion is that the course relies on an unreliable platform for Jupyter Notebooks. Several times I wanted to access my notebooks to continue with the course and got a lot "Bad gateway" problems and slow responses in general. It was frustrating because the best part of the course are on the notebooks.

Overall, a very good value. Introduces new topics in Data Science well. Although the Capstone is suitably challenging, I still feel as though there must be a different format to help solidify the coding syntax for python pandas so that the learner doesn't have to rely so much on referencing StackOverflow or previous lessons. Those portions of the code remain a lot of cut and paste rather than truly building the knowledge base.

To whom it may concern,

the course overall is very targeted to useful tasks and knowledge. One thing that could be improved is the final project with perhaps several options that are more specifically defined than the current form of the project. I understand that this will encourage copycats to participate. Another thought would be an interaction with other peers.

Thank you for the consideration.

A good course but this last "Capstone" course takes a lot more time than is allocated. I had to look up many Python coding instructions and do a lot of research myself. I feel like the initial 8 courses do not prepare you sufficiently for the final assignment. I probably spent twice the hours allocated on this assignment but had a great feeling of accomplishment at the end.

Some material was a bit too basic, and not all subjects were covered in enough detail for me to feel completely qualified to jump right into data science work professionally, but this was a fantastic series of courses to get familiar with data science concepts and workflows in Python. It's given me the tools and knowledge to continue learning more on my own.

This course is great as they give you a guideline and teach you how to approach the project. I like how it was open-ended and you can decide on your own project scope so it's up to you on how in-depth you want to go. However, perhaps more help and guidance could be provided as open-ended projects means there's too much to explore on your own

If you are expecting a follow the leader style class where they go over a methodology and you follow behind, this is not your course. The teachers go over basic stuff in video and challenge you with much harder problems to make you go out and find answers on the internet and delve into you problem deeper.

Very good course. There were some serious downtimes in the IBM Developer Skills network which delayed my progress significantly 5. I had to extend my course time by a month and the next month's fees kicked in. That said, it was a great experience doing this course and the professional certificate overall.

A real challenge! There were moments of frustration, particularly when libraries wouldn't work on different Jupyter notebooks. However, I have learnt so much. All the courses in this professional certificate have prepared me well... but there are also some very knowledgeable people in the data community.

I think that the geocoding and APIs need to be sorted out much better. You should not present students with location APIs, like google, that do not actually work, explain that they are available intermittently, then give them a csv file and call it good enough.

Valuable course to know more about Foursquare API, but short in content (more focused on assigning a final project). Maybe more tools or even templates for reports and/or presentations would make it more useful.