As a disclaimer, I have previous experience with SQL, Excel, and Python. The SQL and Excel material taught in this course left much to be desired. In my opinion, the amount of material given for SQL and Excel is equivalent to coming into contact with either program only a handful of times. Having taken only a single short course on SQL using LinkedIn Learning, I was more than prepared to learn the SQL taught in this course, and the basic Excel functions would be more suitable for a computer literacy class. That is not to say that the instructors are incapable of sharing knowledge, but they have a unique ability to dive deeply into each subject to ensure that the student has a profound understanding of the topic. As a beginner, the information for R Programming and Tableau were exciting and informational, and - again - the instructors seem to be knowledgeable of each subject. A few complaints about Coursera directly: the Modules are inconsistent about whether or not there is an "End of Course" exam, the videos restart randomly and some are missing their transcripts, and several of the "attached files" available for download are not actually available for download. This course specifically, as produced by Google, attempts to drive the user to a Google based platform at every turn, and the exercises on Big Query are no longer supported (this was especially frustrating). All in all, I feel like the knowledge I gained from this course was still worth it. If you don't do it for the Excel or SQL, do it for the RStudio and Tableau experience, and do the capstone. Finally, this course does not take 6 months. The time estimates are completely inflated. Thanks for reading, if the comment allows for feedback I'd love for it to be housed here.

For the first half of the course, most of the material covered I was already aware of, specifically regarding spreadsheets, meaning the beginning was a little slow and I don't think I learned much new. It would have been nice to have 2 tracks to choose from, a beginner and intermediate track since most people have come across basic spreadsheet functions or some form of coding in their academic/professional career. I also did not always like that all the tests were in multiple choice format, I wish there were more questions included like the ones where you have to perform SQL or R code in order to answer the multiple choice. Additional to the individual project it would have been nice to have some sort of "graded" case study, which, similar to the end of each course exam, leads you through a small project, requiring you to use all the skills from every course in one exam, whilst still guiding you a bit through the process. Then I think it would be a bit easier to get started by yourself on the Capstone Project.

What was also a bit of an issue for me on a Mac was to match some videos in full screen, there was then not an option to rewind the video, the full screen always needed to be exiting, that was a bit annoying when one wanted to see the applications used in full screen.

Overall I thought the level was a little bit too easy, I do not think I would be comfortable applying for a juniour analyst position with this certificate alone, which is what the certificate is advertised as. Again, maybe having an intermediate track for people to have to chance to skip over the basics and go a bit faster into the complex aspects would be great.

The capstone case study is a good idea to capture all that was taught to this assignment and use the assignment as a portfolio. After spending hours with Tableau and R I could not remember what to do or how to start or approach the case study 1 bike-ride. I know Tableau and R is necessary to create the portfolio however I spent so much time on the course and they were at the end of the other modules that I forgot what to do. Now I have to review the course again to complete the capstone. My recommendation about the format to complete a capstone would be at the end of ACT the capstone be given to complete while these modules are fresh in the mind. Then have Tableau module followed by the same capstone to add Tableau. Then R module followed by the capstone to add R. This is a better approach because at the end of each module you build on the capstone case study while the course is fresh in your mind. Also, there was mention of a checklist in one of the lab learnings that I think would benefit students to keep track of what do first at the beginning for the course rather than somewhere in 4 or 5 module. Lastly, the Course Challenge ought to be reset after 5 hours instead of 24 hours later this too long a wait to return to complete the quiz.

Overall very good at the high level and moves chronologically in a way that makes sense. It gives a good framework for understanding how to understand and analyze data problems and the videos are very helpful. Because its a course that covers a broad spectrum, it falls short when it comes to some of the nitty gritty and the learning curve with respect to Rstudio and SQL. Specifically there were some basics that were missed in the SQL section that make the more advanced sections confusing so have supplementary learning materials ready for this section. BIG Query is also less intuitive to use than say, MySQL workbench. For Rstudio, it wasn't bad but again, some of the basics were glossed over that could make some of the more advanced topics confusing so have supplementary materials and youtube videos at the ready to fill in the gaps. Overall though, the course mostly strikes the right balance with respect to the three tools, how they interact and how to use them as well as their strengths and weaknesses. I felt I was able to combine Excel, SQL and Tableau very effectively to create a coherent case study for the capstone project and the additional resources related to job search and building your profile are extremely helpful.

good for an junior data analyst and have to be nice internship for the people who have opted for this course and to get it easily when they have to complete it in less time also. They have a lot of case study being learning is an important factor for this. And then by clicking submit you must agree feedback may be viewed by the coursera community for the compliance of the profile privacy is being done. junior data analyst and have to be nice internship for the people who have opted for this course and to get it easily when they have to complete it in less time also. They have a lot of case study being learning is an important factor for this. And then by clicking submit you must agree feedback may be viewed by the coursera community for the compliance of the profile privacy is being done.

There is always room for improvement. I do think this course needs to be updated. Requirements need to be more clear. There needs to be better visual examples and links to helpful hints. Communicating in the forums seems arduous, and getting responses with well constructed sentences was next to impossible. This is not a criticism, but an observation. One thing I really wished that was available was a link you could click if you got stuck and you could see better examples of what to do. Having a button that says, "If you are stuck, click here". I know the objective was to see things in new ways, and think for myself...and I often felt that a little more guidance was warranted.

Anyhow, thanks for making this possible for me to learn something new and exciting.

Overall, I enjoyed the learning experience. I did find that the data files were much larger than what we had used in the past, which created problems when it came to uploading them into BigQuery and Google Sheets. I was able to make do, but in ways that weren't ideal in terms of making use of the tools we had learned throughout the other courses. I wound up performing all of my analysis in Excel.

I did feel like the interview advice and simulations were helpful, and I appreciated the reminder about the pipeline of companies hiring out of the course completion, which I had forgotten about.

I enjoyed the content this programme offered and the online practice was convenient too. There was one thing I would suggest Coursera and Google to improve which is the online test. There were a couple of times when I tried to redo the test, the page couldn't be refreshed successfully and therefore in the end I had to wait for 24 hrs due to repetation. And also, when doing the programming or SQL related tests, the pages sometimes couldn't run properly so I was confused that if or not I entered the wrong answers but in the end my original answers were correct but the page didn't work.

Overall I think it could have been a big harder - I was actually disappointed that no one would be looking at my capstone project and grading it. And I'm slightly annoyed that the capstone project I chose had data sizing issues that exceeded the systems I was supposed to use to analyze it - I wasted a lot of time trying to make things work when eventually they didn't. But otherwise the rest of the course was fine. Most of the module topics I was already familiar with. The R Studio content could have been swapped around a bit for better understanding. But overall it was very helpful.

The dataset used for divvy bike was too large for platforms like R. That was the most difficult part of the project. Rstudio would crash multiple times anytime a month that had a lot of entries were used. I was able to complete the coding but after many attempts. I think for the purpose of the capstone maybe using less months of the data would be more useful. I think the amount of data has increased since the beginning of this course which may be why the issue didn't exist before. Otherwise the project was good and definitely had me sharpen my r programming skills.

The module featuring the Tableau tool could have dealt with the topic in much more detail. Could have shared a bunch of examples ranging from easier ones to the tougher ones with at least the scripts for adding new columns and including and manipulating the visual elements documented and shared. Some challenging problems or an optional section to try out some challenging codes could have been added. Also, notifications to remind people to at least spend 15 minutes with the course would be awesome.

Great beginning introductory Course! Although, employers desire numerous other skills besides what is offred with this google certificate. More coaching needs to be available in order for a student to become proficient in the course work provided. I would be willing to pay more for one and one coaching that would help me to succeed. I felt numerous HR professionals are setting the bar too high (time goals) in order to receive people who might be proficient in the course work provided. Thanks

The capstone is quite a great exercise to go through what I've learned in months. I strongly encourage Google to add more capstone-like exercise in each course so that students can have a down-to-earth case studies and solutions. The only weakness of this course is that the datasets and the question of capstone are not articulated enough, as well as the reference solution. Thus, It took me time to guess what exactly the definition of the data column and what can I do beyond the reference guide.

Not bad. I finished in 3 months. You do get an intro into SQL, R, sheets, tableau, etc. Check out some other options, though. Perhaps think beyond the certificate you earn at the end. You can learn much more productively with slightly less guidance and more personal initiative. I.e. print out the R(programming) guides straight from CRAN and learn that way instead of watching a bunch of tokenistic video tutorials. Just an example. For the price, it's worth it.

Informative and very helpful. However I thought that more instructions and info should of been given when covering coding languages. Also more insight on how things are set up and work, in some platforms, should of been given. I took notes on literally everything but felt unprepared when the capstone project came my way. Definetily will need to reach out to other resources whilst I continue to code. That said, a lot was covered and I am happy.

The reason I am given a less star is only because, I wanted a feedback or one-to-one video feedback with expertise about how I did the capstone project, so that I could apply better efforts in future. I also noticed doing this course didn't help me much in getting work opportunities. The best part were the instructors. I also liked the mock interview conducted for understanding of better approach in regards to interview and resume.

This course was a strange and wonderful mix of technology and art. This is a great start for anyone interersted in Data Analytics. That said, the technical content on SQL and R is very introductory and very repetitive - it doesn't build enough, and, honestly, doesn't give a solid enough foundation to tackle the capstone. You will have to do a significant amount of learning on your own to be able to complete a worthwhile capstone.

Overall it is a great program, they teach you the basics to get an understanding of what data analytics is. One issue is that they introduce a program early on and then they don't come back to it until the end. There are refreshers but you would think it can all be done at one time. It is also easy to get lost between SQL and R and remembering all syntaxes. Great introduction course and great for learning at your pace.

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I will keep my review short and direct, I learned a lot of new things as a beginner in Data. The course is designed for those who have no knowledge or experience in data in general. Some courses are basically "common sense" and I wish I did not spend that much time on them, but they might be helpful for other people. SQL and R are amazing and I needed other resources to learn more.

I think that this course was great for introducing the concepts of data analytics. I do believe that more hands on work starting from the beginning - with a step by step approach to building up a complete case study- would be beneficial. Completing that and then starting an independent case study would give one a firm basis for completing the steps of an independent case study.

Everything about the Google Data Analytics Certificate program was excellent—it's truly been a great learning experience. The hands-on projects and case studies were particularly valuable. Looking back, I would suggest considering Python as an alternative to R for future data analysis work, as it offers a wide range of libraries and is highly versatile.

A lot of information that can be helpful or disorientating. I enjoyed the challenge while I was working on it. I would have like more ways to practice the skills without step-by-step instructions. Raw data and answers where we had to find our own way to those answers. Trying to make up my own problems to practice with was outside of my capability.

The training is great but some how incomplete. It would be greatest if the training included some statistics fundamental concepts like variable types, measurement scale, distributions, descriptive stats and hypothesis testing, source of data (primary and secondary), best practice of primary data collection. The capstone project is Awesome

When taking the tests, there were times where I would answer a question right and it would be marked wrong. When I retook the test again and provided the same answer as before, it said it was right. All and all, I have learned a lot and I do feel confident in what I know. If I can say anything, it would be thank you Coursera.