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.

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

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

Too project and presentation oriented still informative.

too much attention to Job etc than learning Data Scince

Voice too low.

This course should have been titled "How to work in an office at Google". While that's something good to know even if you're not going to work for Google, it doesn't really cover the "Foundations of Data Science" in any meaningful way. Further, the course was full of errors, ambiguities, and things that would only apply in a select few office environments. The quizes seemed to have been designed by someone only familiar with this specific course material and not the subject in general (leading to the above-mentioned errors, ambiguities, etc.) I'm hoping the rest of this certificate program is *much* better as this course was really disappointing.

Foundations of Data Science is misleading (It's foundations of Data analysis). Also to not be able to get the certificate until you pay is irking. Also found some brain washing in the course particularly with coaching. I do like the PACE structure and the communication part.

The course seemed completely useless to me. Very little attention to technical subjects and a lot of unnecessary useless information. Perhaps this is my personal problem, but I formed some expectations based on a course syllabus that were not met.

instead of giving technical tools, this course “talk” about how to become data analyst with many unrelevent data, they also invented” PACE ‘ instead of the steps learned in the basic proficiency

Interactive but very lengthy for no reason. They expanded 4 topics (PACE, RACI matrix, Project proposal and Executive Summaries) into 5 modules. Hoping for better.

This is very obvious stuff for what is the ADVANCED certificate. It felt like a waste of time for the most part, but the PACE model was okay.

Format for South African national ID is wrong