Very informative, steady and understandable... Just wish I can remember all the points made

Extremely challenging incredibly for beginners yet rewarding.

too deeper information. lab was nearly impossibles

it's a good course for begginers

Good detailed

Thanks

good

I would like to share a few observations. Firstly, the course is heavily focused on statistics, which might be challenging for someone specializing in mathematics. Additionally, in the final project, there is a notable absence of coverage on data engineering, despite appreciating the overall content. Upon completion, the course effectively covers a substantial portion of data science, but it would be beneficial to include more on data engineering.

It would be of a great help if there is a video of someone explaining more on how to do the end of course projects. There were so many Phyton commands that was not discussed in the course but was later required in the end of course project. This seems to be a steep hill to climb coming from a non-CS background.

It's ok, but worse than previous courses. It's confusing to listen to the instructor when it feels like she's just reciting from the screen. In the previous courses I felt like the instructors were experts.

The topics discussed were amazing but would have loved to dive deep a bit into Anova, Ancova, and other hypothesis testing.

Transcripts have many mistakes. Good course otherwise.

This course touches on many topics. The problem is that It touches to lightly. There is a very wide gap between the videos and lab work. Adding in smaller question sections would making learning these topics easier.

the concepts are badly explained and requires a lot of work on other sites to understand what is currently happening. Some videos don't make much sense.