Some parts need to be updated

too long and a little boring

Not enough Tableau practice

Contents are too general

Good beginner course.

I want more Practice!

Too many explanation.

It is very important

I miss tableau

Awesome course

poco practico

informative

Nice course

very basic

it is good

very good

reliable

not bad

Good!!

good

good

ntg

I'm not impressed with the course nor the certificate program at this point. The quizzes test your recall of terminology but not your mastery of the topics underlying the terms. There's no opportunity for you to demonstrate what you learn with respect to visualizations and the whole community feels disconnected and aloof. Lots of the forum posts are people phoning in discussion prompts and that's not really their fault; the course phones it in as well. The content is shallow and doesn't foster mastery through practice, repetition, or demonstration. You can click "complete material" all the way through the course, guess the answers to the challenges, and get a Google certification in a week. Don't make the mistake of thinking this makes you as good as a Googler data analyst though; this course as taken is blatantly in its beta-testing phase.

It would be great if we had graded submissions where we could make our own visualizations, presentations, and show our mastery of data analytics so far. However that would require the Google Career Certificates team to have a team of competent and dedicated proctors and they seem to only have the budget for a couple forum post answerers. They don't have enough people to manage their course or student community.

The video lectures have odd pacing and some seem edited for brevity or to support a specific narrative. Lots of the practical video lessons are "monkey-see, monkey-do" video tutorials where the instructor demonstrates their expertise and directs the student to follow along. At the end of the lesson, the instructor claims "now you know how to do X just as well as me." As if copying them once gives you the same level of mastery.

It's not all bad, though. Lots of the principles here give you solid foundations on how to be a quality data analyst. The topics covered here are an excellent jumping off point for independent study and (ironically) googling the terminology used in the course, taking notes, and incorporating it into your knowledge base makes for just as good an education as the Coursera course.

Overall, this is a passable course with the potential to be great, but just isn't worth the money I'm putting into it. Since the course is newly created, I feel as though Google is testing the course using the first batches of students. That's a jerk move since I'm getting a bad education in order for future students to pay the same amount and get a better one. It seems like a software strategy for iterative development / sprints / what-have-you. Speaking as a data analyst - this course won't make you a good one. It'll just about give you the bare minimum, but to have a good shot at employment you'd better use this as supplementary learning, buy a book, and do plenty of independent study.

I have mixed feelings about this course. My main problem with it is that it just didn't fulfil it's assumed goal, which is to teach visualizations. There are very few Tableau tutorials in the course, and the ones that are there are more like UI overview (incidentally, the UI has changed a lot with regards to some important elements like joins). The tutorials are extremely guided. All in all, this part of the course really failed to live up to the expectations. You won't learn Tableau - and you won't learn data visualization.

I also didn't really like the personality of the presenter, sorry! But it is an important factor for the enjoyability of an online course.

On the other hand, the course had unexpectedly good material about presentation skills and building a strong presentation. For the first time in six courses, I found myself downloading actual videos for further reference, and I can easily picture myself going back to these materials when preparing presentations for my future work.

Tableau is good tool for Data Analyst. After taking this course I think it ought to be given after the CAPSTONE. There is too much to learn here and having taken it , it leaves me fearful that I have done some data dumping of all that I learned previously which is probably more relevant to the CAPSTONE than this. R is right after this another useful tool for DA but is it necessary to have it right before the CAPSTONE adding to more data dumping of the previous 6 modules completed. If and when I do get to the CAPSTONE and these 2 modules are not in the capstone I am going to be deeply upset . My recommendation is to you are: 1 - have Tableau and R modules after the CAPSTONE. 2- create a separate CAPSTONE to cover them 3 - issue a CAPSTONE for modules 1-5/6 followed by Tableau and R modules. Just saying, right now Tableau and R is consuming too much of the real estate in my brain and I know I have already dumped modules 1-5/6. Please consider my recommendations.