The course material is ok (a bit to basic) but personally I don't like robotic teaching. I prefer to see the profesor during the online course. The last assingment isn't very well explained and is a Little bit confusing the section of grading peers with the section of complet

The Peer Assignment did long go along with the lessons. It was almost completely unrelated. You need to include a lesson work with XML if that is going to be the Peer Assignment for this course.

The videos need to be updated. The audio and video don't match for some lessons.

The labs did not always function properly, I found the external sites to be spotty (both IBM and the python lab site) as far as their reliability. I suggest that for the python labs that there be an alternative like downloading Anaconda to run Jupyter notebooks locally.

With all due respect to everyone involved - this exact course is horribly built, buggy and not explained, like at all. The level is not for beginners. I want to add that it would be very helpful to have a link to file examples to understand the concept (e.g. XML, CSV).

I was not impressed by this course and felt the actual Python learnings were very superficial. The videos were very quick and hard to follow despite of the fact that I have a basic knowledge of Python already. Based on my experience I would not recommend this course.

This course has very limited exercises after week 3. Pandas and Numpy are covered in a nutshell, without much details and exercises. Web scarping sections were messy and hard to follow. Hope Pandas, Numpy and Web scraping sections will get improved in the future.

authors have really bad programming knowledge. `File.append()` called "attribute, `\n` called "Python command", some variables named as `FileContent`. I really hope all Data Science related courses on this track have better quality. Total disappointment so far

more improvement in teaching can be done as only 3 quiz was there in most of the section if quiz from each topic should be present in my way min 10 question should be asked whether passing criteria can be reduced because when we do question boost our confident

There's a lot of potentially useful information. However, the course materials are weakened by fast and superficial coverage in the videos, typos, code bugs in the Skills Network Labs notebooks, and the complete lack of context and even experience coding.

Ramps up too quickly in the "classes" project. Also, the read/write lab doesn't work - "exampletext2.txt" (or whatever the exact name is) doesn't load so I got even more lost there not being able to go through that notebook without errors at every step.

This program is not very beginner friendly! The lectures are to short, the problems they give you are incompetent to what they teach. This program will give you the bare minimum and then expect you to solve this mid-level problems during the lab.

Only useful if you have supplemental material on the given subjects or some prior grounding in Python. Subjects in weeks 4 & 5 especially were rushed. Occasional syntax or possibly deprecation issues in the lab led to inability to execute code.

The video lectures barely scratch the surface of Python's capability and the notebooks are littered up with advertisements.

Also, the quizes do not show up the right answer in case you made a mistake.

The final assignment was interesting though.

Some of the content is out of date (referring to Python 3 in the final assignment). The videos for the more advanced topics are of low quality and run through the topics far too quickly. Don't come out the other end filled with much confidence

github instructions page never did load, python external jupyter hands on lab didn't load at times and there is no help desk, no email to approach for assistance!

webscraping part of the course is difficult to understand for the coding part.

This moved way too fast for a beginner—while the quizzes and final project were reasonably simple, the labs were WAY too complicated, and this seems like a common sentiment. Would not recommend unless you're experience in Python already.

Although helpful in parts, as a whole it is not a great intro to Python, I consistently felt over my head after about week 3! An existing knowledge would definitely help as the workbooks are not suitable to brand new beginners at all.

I'm halfway through and the lab notebooks just don't work at all. They load and load but never actually open. I've now read a bunch of other reviews saying the final project is a nightmare, so I'm not going to waste more time on this.

The videos are too short, much of the work is left to self-learning. Youtube videos are way more explaining and they are free. If this specialization claims that it is for beginners, then videos must be more explative and longer.

This course does not prepare you to use python outside of IBM's platform. It makes no effort to teach you how to use any of it's libraries of functions outside it's Watson nonsense place. I know less now than I did when I started.

Was quite the challenge. Without the help of peers, it would be impossible. Course content compared to the assignment were very different levels of difficulty. Assignment was much more difficult. Instructions were somewhat vague

The overall course is decent , it could have indulged in a deeper python understanding but the exercise were fine.

The final assignment in week 5 has no explanation or resource and is just left for the peers to do on their own.

All the labs were broken, I spent time reading the labs when I could but most gave me a error. I looked the error online and it was happening for a few people. I waited at least for the week to see if the error would be gone.

this course was the worst so far in the IBM data science certificate. There were so many inconsistencies b/w the videos and labs and quizzes. Additionally, the videos were edited in a way that left out important information.

Explanations were ok, but almost no real exercises, quizzes are far too easy and the final exercise was also absurdly simple. Courses need to have more exercises to give students the opportunity to really learn the material.