Son demasiados los errores. Especialmente en las etapas de evaluación, la traducción automática hace desastres y a veces es difícil identificar la respuesta correcta o incluso entender la pregunta. En el módulo de webscraping incluso hay errores en el código. Por otra parte, no hay siquiera menciones a IA.

The course is too easy, there are not enough examples for self-practicing. The examples should demand enough effort to get rid of people who are just "certificate collectors". After all, the value of the certificate will be almost zero, anyone how just wants and has money to pay the fee is able to get it.

Cours intéressant mais pas très concret dans son approche. Evaluation très décevante ne permettant pas de mettre en oeuvre le langage mais encore une fois tournée vers une publicité déguisée pour IBM. Le fait que l'entreprise soit à l'origine du cours ne devrait pas impacter la pertinence de son contenu.

unclear structure, jumping between weeks and modules, for example course went back to process different types of data mainly using pandas after API and scrapping sessions. Even for me as who already has experience with python, it's a bit confusing to understand why the course is organized in such a way.

I still have my paid period access till 31.3.2024 (included) but when I want to have a a look at any hand on lab again I am getting internal server error after clicking 'launch app' for all of them - the message with the dog...so I paid for having 1 month access but that's not what I got...disappointed

This course does a poor job at giving someone a foundation in Python programming. Furthermore, there are a number of mistakes in the lab giving one the sense of very little care being put into the course creation. The quizzes are such low difficulty that one wonders what the aims are in its design.

I feel like there are a lot of holes in my understanding of Pyton, to the point where I am going to take an additional course on Python. I am a little disappointed because this course was advertised as "everything I will need to know for data analytics", and based on this Python course, it is not.

While I did learn some useful things from this course, the videos go way too deep in a short space of time. There is a lot of code snippets on the videos and in Jupyter where there is no explanation what it actually does. There are modules imported in Jupyter with no explanation what they are for.

It jumps to some slightly more advanced code without enough explanation or breakdown to explain how to use it for other things. A ton of stuff in the labs does not work when trying it out for yourself. Seems a little packed with information that should be expanded upon over the several more weeks.

This is too fast and not detailed enough for someone who is new with Python. Also, always trying to plug IBM Watson studio, which is slow and sometimes requires multiple attempts to de-bug. Why wont you let us use local jupyter notebook? There are definitely better python courses on this site

The contents of the videos and the labs don't match. The lab sessions include topics not covered in the videos. Also, not enough exercises to practice. I found weeks 3, 4 and 5 are so advanced compared to weeks 1 and 2. There should be an intermediate level and definitely more exercises.

tools for the cource are not working anymore. for example at week 1 hands-on lab does not open and return the following error:

Service Unavailable - Zero size object

The server is temporarily unable to service your request. Please try again later.

Reference #15.9dba1002.1640601352.678ad23a

The videos are very rushed and don't cover the concepts in sufficient detail. It would be beneficial if real world examples and analogies were used to help explain concepts. I had to supplement the materials provided in the course with information from other websites such as youtube.

Good course but needs a major review. Some things are wrong, others not very precise and vague. Video lessons are often a bit sloppy (misaligned graphics, questions come seconds before the answer was given and the like). Overall feels a bit unprofessional and could use some polish...

Much of the content is quite sloppy, with many errors and poor organization. I was able to complete the course without issue because I am already familiar with the material, but I can see others struggling and not getting much out of the course if the information is new to them.

felt very unprepared for final assignment. Week 5 assignment would only be appropriate if we had a video walking us through, and explaining the specific requests, and the why and hows of each point of the task. then it would potentially be a great way to finish off this course.

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.