it was a very tough course. i have to do some more learning

final project has bugs and errors when running the code

A good beginner hands-on experience for Data Science.

Students had a lot of problems with IBM Watson Studio

redundant examples.. could broaden and learn more.

Jupyter on Watson Studio is not working properly

I think we need more hands on lab practices.

Informational, but too easy.

Good practice project

not very explanatory

Nice but very basic.

Too hard to follow

Encouraging

Good

good

This course has too many issues:

The assignment rates items that are vague: If the quarterly data is demanded, then it should be spelled out and not just "the revenues"! To grade on this is ridiculous!

I was not able to see any links in the reviewed assignments - but I am starting to suspect I cannot see the Watson links! I could not get a Watson account, as the creation failed repeatedly despite me trying to troubleshoot it!

The used python version is old. Methods such as .append() are deprecated now! Also, who uses that python version locally? I would need a new env just for the course...

Some installs or imports gave warnings and failures, for example, for not using the version the employed jupyter version was expecting.

I got full marks despite some misunderstandings due to the vague new(!) text, because the people apparently seriously had enough. I am angry and embarassed that I deducted points in my reviews, as I followed the stupid guidelines! Do note that the new assignment version has new and vague texts. I lost all my previous work when it was updated too. Since it was some time I did it, I could not remmeber the quarterly shennenigans, for example. Kindly do not ask me to repeat this stupid assignment by changing the tables to quarterly, this is utterly repetitive. At least the weird tip to take the [1] (second) table now makes sense again. I marked it as an error in my notebook, as the yearly was demanded by my understanding of the text!

The exam should have been a new problem with at least some slight variations. It should be clearly spelled out what is expected.

I don’t Understand why this is a standalone course instead to be a part of the course on python for data science, most contents are in common and here they are just repeated.

Main lab (used for final assignment) is too easy and guided, most questions say also how to do easier tasks (e.g., get first/last rows of a dataframe), thus it is not challenging.

At the end of the lab I was expecting a discussion and explanation about the meaning of downloaded and plotted data. As said before, explanation is an important part of the data science methodology.

Outdated code that doesn't work properly in watson studio required for the final project. The function they wrote and want you to use to make a graph is unusable. This means that after completing the project on watson studio you have to go in, transfer the project to your local machine, and run the code there. They need to retest their course material in their chosen platforms. There's no reason that it should not work in IBM Watson Studio as this course is being taught by people from IBM.

Could really use more than a few examples for different parts of the project. A couple of examples of where the graph was used would have also helped. I think at least one extra week of prep for the project with a couple of examples would have helped greatly. Also, I am new to this type of coding I know a little html and php but for me it would help to not only see single lines of code but a full page of code to see how it would run or execute all together.

Too much information is presented at once without being given time to absorb it. Not enough practice with the topics presented. Some topics are just glossed over in a couple minutes. I had to visit other tech-related sites to figure out how to do some things that were asked in the final exam, since the IBM lessons didn't adequately explain them. The speaker's voice volume is inconsistent from video to video.

Good content but light on programming fundamentals, so defining functions and how calling them works are absent. Be wary of a steep learning curve compared to previous courses if you aren't already a programmer. Much worse, the final is just actually broken and your passing is up to luck depending on who reviews it and whether their browser will properly display the charts you work to create.

The whole making of a dashboard by screenshotting graphs and pasting them places is just poor, noone makes dashboard that way in 2024. Why learn to do it that way? Also too many instances of just copy and pasting code from earlier places, but the dashboard forcing you to remember the exact syntax in every new section, if its not new, just put the code for us with gaps for what IS new.

There are some useful practise labs but the code is outdated and the use of IBM Watson seems to have been removed. It seems this is so the instructors don't need to update their code base which doesn't run on recent versions of the libraries or python.

The course format is not clear as instructions have not been fully updated. Poor quality course which could have been good.

You have to review someone's submission to finish the course. The thing is, if there is no submission available for you, you have to wait! You can not finish the class without it! Ridiculous! I waited for a while. But everytime I check, it says same thing: ''There is no submission for you to review right now. Please come back later'' You gotta be kidding me seriously!

Very informative project, however it was also very frustrating. Lab/notebook should be updated to ensure correct source data is provided when the assignment is started. Looking at the discussion topics, the issue I had was identified over 2 years ago and still seems to be an issue. However, following the topic I was able to finish the project.