thank you

Perfect！

Greattt

perfect

Awesome

Brutal

Great.

Good!

great

Good

Good

Be prepared to study really hard for this one by yourself. A lot of abstract information in module 4 and 5. Takes a lot of hard work for this one to truly understand every concept. Final project was also challenging and definitely pushes you out of the comfort zone since many concepts not taught, but will accelerate your learning much more than previous course projects which were too easy.

This course introduces lots of useful regression models for data analysis. It also includes labs for using python libs to compute these models and interpret results. Absolutely fresh experience for me.

Found it a bit tougher to comprehend. More examples and formulas like the 'Logistic Regression' Module would have helped.

Some advanced topics were not covered during the lectures and reading, but overall a learning experience.

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

Extremely challenging incredibly for beginners yet rewarding.

Thank you Tiffany mam for this learning experience.

too deeper information. lab was nearly impossibles

it's a good course for begginers

Good detailed

Thanks

good

Interesting topics, but it's a weird mix of "the technical stuff isn't important, so we will skip it", then proving a single example with some Python code, maybe mentioning certain functions, maybe not. After that, you'll have to code your own stuff, where I most certainly did not remember all the dozens of functions from several libraries that have been used, forcing me to look things up over and over again, turning this into more of a treasure hunt for the right stackoverflow post and simple copy-pasting or re-typing functions and code. I think if a course aims to teach practical skills in coding, slowly build up introducing new functions and methods and be very clear about what a function does and what it does not. I think that a lot of potential was lost here.

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.