A very good first look at Python, Pandas and other basic aspects of Python for Data Science. The course material, as presented in text transcription, could use a good proofreading, but otherwise it is a very solid and useful course.

It is easy to understand the basics of reaind and manage data with Pandas in Python. I think it could be better if we can go deeper into the syntax and objects and methods used on pandas to better understanding of how work with them.

I really liked the course. My only complaint is that the last two sections represent a big leap between learning basic python skills and suddenly using complex APIs like speech recognition systems without understanding them properly.

The content went a bit to quickly for me. I am completely new to computer science, and so all that new vocabulary was difficult to comprehend especially when I wasn't sure how it is typically utilized for data scientists when coding.

I really enjoyed learning about Python with this course. The labs were pretty neat and helpful. The only thing that prevents me from rating it 5 stars are the videos which were confusing at times and made things overly complicated.

Issues running labs. Bokeh does not import, so its impossible to make the dashboard. Notebook would not recognize the bokeh module no matter what I did. Had to download Anaconda and a computer side service to run the lines of code.

The overall is good, but I wish this course needs to improve the interaction between learners and the Jupyter Notebook. It's kind of boring sometime when I need to only press Shift + Enter to run rather than typing code on my own.

Syllabus is well designed covers all basic concepts of python and if you already know a little python you can easily complete this course without a fuzz.

Thank you IBM and Coursera Community for this . I had a great time learning.

A solid introduction to Python that I personally found very useful. The only issue with the course is the abundance of small errors throughout the materials. Final assignment requires a bit of debugging and tweaking to get right.

The review of python basics was nice. The actual AI or data science part was only covered for a fraction of a week, so not much was gained in that regard. Also, it felt like a constant plug for using/buying rights to use Watson.

Good level for people with little to no programming experience. Very quick to complete (can be done in 1 sitting). But gives an idea about how to work with datasets, different libraries and feeds well into the following courses.

Introduces the most important features of Python. Quizzes were rather simple. The final assignment is a total mess. Without information posted on discussion forum by other learners it would be impossible for me to finish it. :-(

The first four weeks are very helpful, and then week 5 is the project. There is little to no assistance in week 5, it's more-or-less sink or swim, but it forces you to apply what you've learned. I felt like I made large strides.

This course is well structured and easy to understand even for those who do not have a programming background. Only thing that I see needs improvement is more challenging lab work or assignments to help the improve the skills.

IBM does a good job in doing the python introduction for beginners. The use of Watson studios an Jupiter notebook is good although the platform on itself can be a bit confusing at times.

all and all... great experience for me.

A great introductory course, I learnt a lot in a short time period. The labs were key to understanding the course content and for taking notes. All of the labs took me significantly longer to complete than the estimated time.

The hands on labs are very informative. Its not that difficult to complete the course if you are focused, attentive and curious.. the quiz were a bit tough with the passing percentage kept so high. great course for beginners.

The Python course is very useful and I loved it while doing it. I want to say one thing i.e I learned a lot from this course and I upskilled my level in Python by doing this course. I recommend everybody to take this course

It would be very helpful if there were notes for each video that contained the code discussed -- both for the sake of learning, but also for people with visual impairments who might not be able to see the code in the videos

such a wonderful course threshold for students, Indeed i got some idea about data science and what's the data science domain dissertation within python . Eventually this course gave me conception and notion of data science.

Hay preguntas mal redactadas y preguntas que tienen más de una solución que te afectan en el examen final. el curso en general fue bueno, pero pienso que podria ser mas friendly para los novatos o un poco mas intectactivo.

Great, but some of the labs could be edited for better grammar and descriptions. Could not complete some of the Watson labs because my api keys would not work for some reason and I did not know how to go about fixing that.

The curriculum is too good.But at final stages it became complicated and started to confuse.Felt that there could have been a little more documentation to make understand at the final 2 weeks.But great course.Learnt a lot.

The inner workings of the project (dashboard creation process) are not that clear. May be an optional reading can be added for interested students to understand the dashboard creation and the libraries used in more detail.

Understanding the Final Assignment and its instructions were a bit tricky. May be an introduction to IBM cloud hosting and the significance of various credentials required in the final assignment will make it a bit easier.