While I learned a lot in this course, it could have been a more enjoyable process. The videos and labs basically had the same content. However, the labs are a better learning experience (can run code and see results) but come later, making them less valuable and boring. Please consider having the lab content be more unique, as it was in the previous course. Also, please update the materials as Watson Studio changes.

The videos and labs were helpful and the course does help one learn some Python fundamentals. However, I believe that the labs and quizzes could have been improved. More exercises within the lab environment would be beneficial to promote learning. The weak point of the course is that the tutorials for using IBM Cloud were weak. More information and walkthroughs (including videos) should have been provided.

Good content overall but weird level requirements; the course covers too many basics for somebody who already programs but also assumes a lot and therefore is not adapted to someone who has never programmed.

It relies on external platforms that will not always work.

Instructional and useful nevertheless, recommend if you're already familiar with data analysis (in R for instance) and want further knowledge.

An adequate python crash course. The level is good for complete beginners. People with computer science background will find this slow. Also, the labs and the lectures are completely redundant, they almost match 1:1, except that the labs often fix a few mistakes in the slides. Don't expect a great numpy intro: you will basically get array creation, indexing and slicing and basic vector/matrix operations.

I am new to python I used it for the first time in this course. I found the course to be well organized. I liked the labs and how they are organized and well written. I found the course to be hands-on which I needed. I did have some background using MATLAB and found that to be useful, however, there are some differences in the syntax and the data structures.

There are not many self-learning assignments

The videos are quite good though the pace is a bit fast. There is a disconnect between the labs and videos are concepts are introduced in the labs which are not covered in the videos. While the students are probably not expected to understand these advanced concepts and just perform the exercises in the labs, it does affect the learning experience. Suggestion is to try and make the labs friendlier.

I would have given this course a 4 star rating if they had created the final assignment which would have make some better sense in terms of what this course content and course it about.

The assignment had no concept which was explained and in the course and it gets very difficult to understand the assignment. Never been through such a poor one in my entire 15 years career. One of the worst course.

VERY HARD for someone with 0 background in programming. The video felt rushed and didn't explain in concept but rather throwing the subjects right at your face and you need to figure out a way to memorize and apply each of them on your own. Some lab exercises aren't even mentioned in the prerequisited videos... Overall not a fun experience for a beginner. But still managed to learn the basics.

Overall, the course is ok. The first half of the course is manageable especially for someone who has experience in other languages. But the second half felt crammed - it is more syntax heavy and with few drills here and there. Reading the materials will make you say 'wait, where did this syntax came from?'. I believe this can be improved by adding more drills in the 2nd half of the curriculum.

Even it is a nice course to start at Python focus on Data analysis, I hink that the influance in IBM Cloud is too big and take te initial push of the first 3 chapters. Also, if they want to put the focus on that cloud, a more extense tutorials will be needed in that course (mostly, I had to search th "know how" of many elements, wasting time).

Overall, it is a good introductory course to Python.

I wanted to rate this course more highly. It starts well with a general introduction to Python, which should be helpful for anyone who needs to learn the syntax. Unfortunately, the last week or so of content (related to APIs) is rushed and disorganized. Would recommend spending more time on how to build web scrapers, load/interpret data, etc. Maybe add another week of content to the course?

This is a great course to get your feet wet with the concepts presented. But, the "hands on" labs are 95%+ done for you...not much coding on your part. Take it for what it is, take decent notes, and save the labs for future reference.

Advice to Creators:

Go thru the course, ESPECIALLY THE LABS, and update instructions, coding, and screenshots. Some things have changed since you put this up.

There is a lot of in depth information and resources shared about the Python programming language, but I do not feel confident in my skills after taking this course. It is a good start, but there is not enough practice or hands on application of writing code. The course compromises mainly of watching videos and reading code. I don't know how to code anything after completing this course.

Some labs exercises were no explained thoroughly, including more advanced coding and some commands that were not covered a 100% when completing some of the labs. In my opinion, in certain instances, this course assumes that I had previous knowledge in Python, and some of the lesson and topics were explained in a fast pace manner, so I had to pause it many times to understand the code.

Warning for those whose native language is NOT English: These IBM Data Science courses are in DESPERATE need of review by a native English speaker. If English wasn't my first language, I can only imagine how much I would have struggled. It is pretty unbelievable that they expect people to pay money for courses that have so many many grammar, syntax, and audio transcription errors.

The course was well planned however the pace of commentary in the videos was most of the time very fast which resulted in lack of understanding . In addition the Hands - On Lab was not available for a few days causing delay in completion of the course. I suggest that instead of making a commentary in the background while displaying videos the instructors should present the lecture.

I am taking this course as a part of IBM Data Analyst Certificate. The program became suddenly and irrelevantly challenging with this course. Why do i need all these stuff? And the things are passed so quick that it is impossible to catch up with the speed. Doesn't tell properly why sth is done in order to do what. It does not teach the logic but rather it enforces memorization.

This is course is a primer to Python and some libraries used for working with data. It covers some of basics of what certain tools can do for you, but doesn't really cover how to think or plan to do things in Python. If you're already a programmer maybe this will be sufficient, but if you're new to programming it may not give enough of a foundation about how to think in python.

There are some errors. Additionally, I couldnt get some of this code to work on PyCharm. It isnt much help to learn code in jupyter notebook, if I cant figure out how to install these libraries and use this code in PyCharm/Python. ALso, that Watson lab about language translation seemed to be more complicated than it should have been. I dont think I was prepared for that.

The course in general was quite good, but it is full of typos in the labs and to be so much time online and still have so many errors speaks very bad of the service that IBM/Coursera have contracted to moderate the course.

On the other hand, the fact that the videos and the labs say the same thing makes either the video unnecessary or the first part of the lab useless.

Pros: Concise, Informative, to the Point, Hands-On

Cons: Videos narrations were linear and fast, but you could catch in the lab of course. Not for once, I did not interact with the instructor. Some content was just mentioned at the end which I believe was having much for weight and could elaborate more.

Thank you for the effort and time to bring education to the world.

The course itself was good but the final assignment seemed inappropriate for this entry level course. Specifically, the final assignment relied too much on pre-prepared code that was not introduced in this course and did not test very much of the knowledge of the course. Overall, the learning materials are good but the assignment wasn't a great end to the course.

This is like an 'introduction to some Python capabilities', as you need to study further by yourself to be able to do anything meaningful. Also, some pieces of code were not explained adequately/ not running on a Windows system. Studying material could be found in the labs section. This course was the first in the series that seemed to me like work in progress.

This course is comprehensive, but so easy. I haven't found any challenge during studying it! The concepts are delivered in a good way, yet the labs are just repetition of the videos. There's not enough hands on exercises. Everything is with the answers and you got not to try by yourself enough. It would be much better if more challenging exercises were added.

The quizes involving API seem to have technical problems after running the codes provided. Also, in the final assignment, the credentials to be used in the optional exercise don't have information on some of the important inputs for the json file such as access key. Also, the tutorial which was specified is this part of the assignment was hard to find