Improvement on interactive aspect

nice basic framework to follow

Its a Good course to be done.

This is very good course

instructors are superb!

great learning platform

Clear enough

Great course

It is good

Great job

Great!!!!

nothing

Thanks

nice

goof

PACE

Good

good

nice

.

I just completed this course. I do feel some of the topics from this course is a bit repetitive from the previous Google Data Analytics courses. Like what others said on the reviews, I do feel this is more of a communication course rather than a data science course. It's actually quite nice to add a end-of-course project at the end of the course - it does reinforce everything that I learned from the course. But the problem is this project is not suitable for beginners like me - for instance, I don't understand what is "compute descriptive statistics" or "build regression model". I might be able to identify the phase for those tasks but I'm not sure are those tasks necessary to achieve the company goals. The end-of-course project is something I'll have to revisit after completing more courses.

Great value of information and a thorough introduction to data science. However, for the end of course 1 project overview, mine changed from one scenario into three and, it's in a way that I can't manage to understand. I appreciate being challenged and I encourage it.

When I'm to create a proposal with information that is not available to me for a first time user, is not for me. slow it down and build instead of speed.

My First course is "Foundations of Data Science" at Google Advanced Data Analytics Course , It teach me to Handle the PACE workflow at any data project, and Guide me to be a great communicate person to all, and Introduce the several website for my studies, and Teach everything on Foundations of data science, I'm say thank to google to teach me with minimal cost of this course "Thank You Google"

Foundations of data science are the fundamental concepts and principles that underpin the field of data science. These foundations encompass a range of subjects, including mathematics, statistics, programming, and domain knowledge. Here are some key areas typically considered foundational in data science:

It could be helpful in upcomming future

I understand the relevance of the information in this module, however it is very dry and not a fun start to the analytics certificate as a whole. I would recommend redistributing the material in this module between the others to make it more bearable and put it in context.