Peer to Peer assignment was confusing and misleading.

I had some programming knowledge (C++, matlab) when I begun this course. It was easy to complete but I tried to make it more challenging by paying extra attention to the details. The questions that popped up while watching the videos were good at making it somewhat interactive. The quizzes were maybe too easy (most of them had only three questions per quiz). I found the labs very helpful, could use some more practice exercises. It felt like a self-paced course, I would like it if the instructors were more involved in the forums and the grading. Basically, the questions at the forums were answered by fellow students (if someone could help) and also the grading was exclusively by peer-grading. All in all you can gain from the course by putting some personal effort..it also makes it easy to just browse through the questions and get a completed mark nonetheless.

I found the premise of this course effective and the introduction to python and everything it encompasses was great. However, the section on numpy the labs didn't work, it wasn't explained why numpy is so useful in terms of matrix multiplications (am sure we will find out but even just a quick blurb / insight to link understanding), there were no case studies in the latter half which made it just information dumping. And the final section on API also didn't clearly explain why they were so useful. There was a lot that this course could have done - fingers crossed the content improves in terms of explaining larger picture too.

A lot of passive exposure to basic structures of Python , but desperately needs more practice examples and more explicit exercises using code. The instructions for the final activity make a leap several steps past what is presented in the videos and asks that you figure out how to do multiple steps of code without any actual practice coding prior to that. Says its for beginners, but does not teach for beginners. Coursera needs something between Python for Everybody, which is super slow, and something like this, that assumes you intuitively get it.

Weeks one to four are good. Week 5 is full of mistakes. You lose a lot of time for correcting stuff instead of actually learning them. The assignment takes double time just because of the corrections in the given instructions. The data that you have to load in order to complete the assignment are in the wrong address! More examples and coding should be included in week 5.

It might give you all the things that you need for programming in AI and data science but dosent give enough practice to make you feel comfortable with what they teach. They could give few assignments to better the course instead of rushing which overloads the information to be understood and remembered

The assignment is so bad that I had to waste at least 1 hour of time just to figure out why the picture was not changing despite me saving it correctly. I restarted the machine after an hour of research and then it got resolved. THe notebook also behaves weird.

The content was good, but as with most online programming courses, there simply are not enough coding exercises to effectively retain the knowledge long term.

Really basic course.

In my opinion it should have more programming assignments and they should be harder.

The final exam had nothing to do with the course at all. Very poorly thought out.

very basic .could be little advanced

In my opinion, this course goes all over the place. The video lessons are thrown at you too fast, it's hard to grasp anything really, It's not well structured at all..

I was fortunate enough to have some basic Python knowledge before this, so I could get a thing or two.

The final assignment should be greatly rethought, even scrapped for something that actually lets people put their lessons to good use. The last two weeks are spent on methods and some basic data analysis functions, which is good and all of a sudden we are tasked with making faks album covers...

A good improvement would be to create an assignment which lets people practice a lot of things shown in the course, not copy pasting some code and rewriting a function...

As the name says, "Python For Data Science and AI", but to be honest, it covers very little learning materials related to data science and even lesser for AI. Every week it makes you sign up for IBM Watson Studio. The worst part is in the final assignment, you are not judged for your ability to write python codes, it judges you on sharing your IBM Watson studio link. The level of the final assignment was quite low as it should have been.

I don't understand why can't we do the same assignment somewhere else. How this low-level assignment be a part of a specialization course? And the slides demonstrating the procedures of IBM Watson Studio is outdated. This must be improved.

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.

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.

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.

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.

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.

T

h

e

e

n

d

a

s

s

i

g

n

m

e

n

t

w

a

s

d

i

f

f

i

c

u

l

t

a

n

d

t

h

e

d

a

s

h

b

o

a

r

d

c

o

m

p

o

n

e

n

t

a

s

w

e

l

l

a

s

I

B

M

c

l

o

u

l

d

s

t

o

r

a

g

e

a

n

d

b

u

c

k

e

t

d

i

d

n

'

t

p

r

o

v

i

d

e

a

m

p

l

e

e

x

a

m

p

l

e

s

t

o

f

o

l

l

o

w

i

n

t

h

e

c

o

u

r

s

e

w

o

r

k

.

Failures in grammar, logic and wording.

too easy

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.