Great beginners course. The only thing I would change is allowing people to see the answer they selected on the quizzes once they have been marked, and providing them with an explanation on what is the right answer and why. Would provide a better learning experience.

the course has many interesting and relevant topics. however, its contents are appear to be way to advanced for someone who has no previous programming skills. i particularly found the week four/five lessons very difficult. i couldnt just get my head around them.

I had some issues submitting the homework. It took me a while to find where apikeys, access_key_id, and secret_access_key were located. We weren't really taught in this course how to maneuver in Watson Studio. Otherwise I would have give five stars on my review.

Very good basic intro. Enjoyed doing the assignment but would have liked some more challenges. Seemed a little odd to spend so much time trying to produce a link to share the workbook while actually completing the questions was very simple one or two lines of code.

I'd love to give 5 to this course, as this is the best Python course of Coursera so far, but there were some issues in the material. For the names of classes you need to use CamelCase, for naming varibles you need to use lowercase. It's PEP-8 and everybody knows.

This course is a nice design for python basics learning and coding practice, I learned how to coding in Python through this course, while there is a few minor errors in the slides/videos, and it would be better to update the teaching videos to the latest version.

The course is friendly for beginners, which have detailed step-by-step guides in materials. Videos clearly explain the Panda and Numpy using animation and language translator and speech to text on IBM cloud gives me a deep impression on using data in other forms.

This is a good course which makes one a good introduction to Python programming language and Jupyter Notebooks as a framework for coding. Although some of the aspects of the course are introduced in a rather scarce way, and do not allow to fully comprehend them.

Enjoyed this introductory course to Python language. The issues with the final assignment was disappointing, but all the other content was great. Liked the breakdown of the weeks and the consistent quiz's and labs to reinforce what you were reading/watching.

Gives an easy way to enter python, but more text feedback should be needed as videos, are 10 minutos long or so, but they have so much information in them.

Also some assignment and jupyter notebooks were unavailable temporarily and took me days to prepare them.

Great course for beginners. You will learn all the basic data structures of Python.

The only but it the "jump" between the basics of Python and the API lesson. There should be an (extra) connecting lesson which links the basics of this course and teaching APIs

In general quite good. I like the Coursera set-up. In this particular course (it is my fourth), I would like to see more alignment of videos, quizzes and the final assignment on Watson Studio.

Still, thanks to everybody who makes these online courses possible!

The course is very well made, It cover everything. Maybe sometimes would be nice make the video a bit longer or make it slower. It felt sometimes that is too fast. There are some grammatical errors in some places, but nothing important. My rate is 4.8 stars

For webscrapping it switch very fast from simple to very complex which is confusing and takes way more time to understand the concepts. One of the excercises that asked to choose and work with an API of preferences it was al most impossible to solve for me.

It´s good generally, but it has a few caveats. There are some jumps in programming concepts, for a beginner course. And some of them are not used in the final project, so they could be removed and replaced with more in-depth analysis of libraries methods.

Good course for any beginner but some codes taught didn't run properly. And I would request to provide more practice exercises for every type where we get habit of application of not just the current concept but previous ones also so we don't forget them.

Very well written, great for beginners and early intermediates. I find the videos interesting and the assignments are great as well. I learned many interesting things in this course already and I started few days ago, nothing but recommendation for this !

The course is good. You will learn a lot. The only area of improvement can be Week 5, where too much material is covered, but less content/information is explained and provided. Overall, the course is great, if you wish to start learn Python from basics.

The course content was concise and easy to follow. The simplicity offered by this course came at the expense of in-depth knowledge, whose pros and cons can be debated. Overall, a good appetizer for a beginner aspiring to explore data science with python.

Very good couse to get started with Python in Data science field. However, the instructor could have added more detailed lessons. Other than that i highly recommend this course to anyone who is starting their Data Science career/ exploring Data Science.

Very good course to learn Python and libraries to work with Data Science, like NumPy and Pandas. The IBM Watson labs need a little more effort to understand and to complete every step, so don't skip previous labs and pay close attention to instructions.

Great course to get the knowlege of the language. I did however find out from week 5 it was too much information to gather and found a few modules tough to understand. I passed on the first try so its been a great course in under a week or 2 weeks max.

The pace of some of the videos is just unsustainable: I could not keep up, even though I have a very good understanding of programming. Sometimes, the lines of codes were displayed for a mere few seconds, with no timie to review and understand them.

An excellent and amazing course, however I want to leave two suggestions that I missed during the course: lack of step-by-step explanations to install and use python, and small practical activities to visualize the learnings on a more realistic scale.

I'm lucky to have coding experience with SAS for about 100 hrs, otherwise I might struggle a lot more on comprehending this course. And one thing worth mentioning, I spent a lot more time on the working labs of week4 and week5 than the suggested time.