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.

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.

I didn't find this course useful for the purpose I was looking for: use data and practice how o analyze it. It was more like glossary overview of role taking on a project. Maybe it just wasn't for what I was looking for.

The content was decent and a good reminder. But it was sometimes a bit fluffy and the instructors give these "motivating messages" that are just there to keep you on the course. But overall a good course :).

This isn't really a foundation of data science as much as it is foundation for project management in a data professional role. There is very little actual data science instruction within.

Many things are repetitive and can be removed. For example "Role of a data scientist" has several videos and reading material, all essentially talking about same things.

Senti que o curso é muito longo para o que tem de conteúdo: poderia ser muito mais enxugado, mas tem diversas vezes materiais se prolongando sobre o mesmo assunto.

I think the course should introduce different tools, software and libraries used in data science. Also, Different data analysis frameworks should be investigated

every course has 7 course it is hard to complete genuinly each course in this duration and please clear your terms

Too much reading that can be done through short videos. Or, those readings could have been more concise.

There is nothing technical in the course. Skipped a lot of readings and discussion forums.

The course is for advanced users. Some of the topics learned here were beginner-level.

I think there should be more technical aspects and breaking down of those subjects.

I really think, that Google courses need to focus in technical skills.

A few questions were asked but the topic needed to be learned.