No jobs. In Week 4 of Course 8, there is the Googlecerts Coursera Job Platform. Some may call it Consortium. It's linked under "Practice Quiz: End of Cert. Checklist." I did a search for "data analyst." All the jobs seemed to require previous relevant exp. or education. Most req. bachelor's or higher. All the Google postings I checked required a degree. Mods are now censoring comments from people who've said this. I therefore do not recommend Google or Coursera until such time as they're willing to address concerns about online ads for this specialization and the alleged lack of entry-level jobs.

wish they could make a video of full tutorial on the two given case studies and guide us step by step. they should make it compulsory to submit the project and let other students grade it and give feedback

I appreciate the enthusiasm of this course's presenter. However, all the material around the case studies, specifically the first one, leaves a lot to be desired.

To start with, each piece of this material feels like it was written by a different person—and it probably was. This creates a significant problem, in that all the of the material is disjointed and doesn't correctly guide the student through the case study. Sometimes two steps will duplicate a piece of the process, and other times one step will assume something was done earlier when it wasn't. There is an almost complete lack of quality control and editing with respect to stitching together the disparate pieces and making sure that a student can follow them through correctly from start to finish in the order they were presented.

To add a further wrinkle, the first case study specifies in the provided guide that the student should be retrieving the last 12 months of data from the database. However, the R script portion was written when the most recent data was Q1 2020, and it shows. As of the time of writing this (I started the case study at the end of August 2021), the 12 most recent months of data comprised several *million* rows in Excel, and more than a gigabyte of data in total. This amount of data cannot possibly be processed in the free version of RStudio or in a single Excel workbook; it might be doable in SQL, but that requires downloading a SQL platform to work with, since Google didn't see fit to supply us with appropriate access to one (like BigQuery) for the sake of completing this case study.

The course guide should have specified to use the exact same months of data that were used in the R script document for the Analysis phase of the case study. This would allow the student to follow that document from start to finish if there was any confusion about how to code the suggested analysis steps. (As a side note here, why on earth is this script document written in a Google Doc? This makes it practically unreadable. It should be an RMD file that could be followed along with, just like in Course 7.)

All told, the main point of this course turned out to be a disaster when I had really been looking forward to it. I was able to learn quite a bit by trying to troubleshoot all the errors that kept arising, such as the as.numeric() function given in the script document turning my whole ride_length column into NAs, but I learned the most by just trying to clean the data myself before I realized that the case study guide offered specific steps of how to clean and analyze the data. So, thank you, Google, for providing the basics in previous courses so that I could still teach myself something when your case study course turned into a train wreck.

I decided not to do the project as it was too unclear, and the datasets were too large. Furthermore, if you chose the R route, you were given the script to use, which seemed too advanced for the amount of R we were taught in the certificate.

I did find the interview videos helpful.

The previous courses in this program do not adequately prepare students for this project, and there is no help to be found from when things go wrong. I powered through the other seven parts of this without incident, which should have triggered suspicion on my part that the instruction was not enough, but I legitimately thought I was just picking it up that easily.

Sadly, a waste of time and money. Too much time was spent on the basics and too little time spent on technical know-how like SQL and R. The videos were boring, the assignments were too few and too pointless, and at the end as I struggled through the case study I realized how ill-prepared I was by this course. To help me finish the case study I started some free Codecademy lessons and learned more there in a few days than this entire course. I thought at least the job board availability at the end of the course would be worth it, but that is a disappointment as well. Unless you live in NYC or Silicon Valley, there is little opportunity to be found there. Perhaps this is a good course for those who need to brush up on their skills, but for true novices it's a big disappointment.

This Capstone could be better and more guided. Case studies given are either too complicated or have very less data.

I was not expecting too much from this class due to the price, so this review is not based on the content, but rather the flow and presentation. For a good 60-70% of the course, you are bounced back and forth between Excel commands, SQL commands, testimonials from Google employees, and data analysis best practices. My notebook looks like 14 people were trying to take notes all at the same time. Trying to go back through my notes to find one particular command or concept was frustrating. Once the course starting covering R, it was a little better but still continued to be peppered with extra videos and distractions. Some of the videos were actually really informative, but how and when they were placed were not helpful to the learning process at all. Also, having a final/capstone project that is not reviewed or graded devalues the capstone project massively. I guess you get what you pay for.

Instead of giving step by step process on a written pdf, you should show it in video step by step so we can perform it by following the process as when we get stuck we dont have anyone to ask what to do I cant ask a pdf copy what I can do if I get stuck.

95% of material is waste of time. 5% actually learning how to analyze/code/clean real datasets. Mountains of motivational bullshit that takes up time/energy and makes courses monotenous. really dissapointed. simply continued to get the progfessional certificate. wiould recommend others self study. while certificate may sound good on the resume you will be 100% unable to do the actual job after this course

Informative course; excellent case studies and some real world applications, however, would be great if there was a downloadable template so students can take notes while reading/watching(not just transcripts but the slides & screenshots on instructor's screen with space to write notes/highlight ideas) This would help with traditional hardcopy people, kinesthetic learners, or those with neurodevelopmental disorders.

Unlike all previous courses within the Data Analytics Certificate, this one is very disappointing. There's a big gap between the skills one can earn throughout the courses and their applicability to the final Capstone project. We have learned general data analytics topics, specific tools, processes, etc. But we were studying them without a chance to look at the big picture - meaning, we were learning every skill in its own sandbox without adding them to the real analytics process. There's no chance to go through the data analysis from start to end similar to the capstone project, but with the supervision of the instructor. Thus, when entering the tasks listed under the capstone, you just don't know what to do. Yes, you know Excel, Google Sheets, SQL, R, and visualization tools, but you don't know where to begin with, how to put everything in order, what you should look at first, second, etc. In other words, there's a definitely missing course or part: a fully guided capstone project. The one in which the instructor(s) guides the learner throughout the project explaining the entire analytic process step by step, allowing learners to make attempts, and providing brief feedback.

This is why I personally have not completed the Capstone although I marked it as completed. I was simply lost in what I needed to begin with, what was next, and so on. Basically, the Capstone is useless for those who have no previous practical experience.

fake interview video and useless tips very very disappointed with last course

This course soured my entire experience with the rest of the specialization.

The instruction on the actual case study is lacking at best, abysmal at worst. Even on the guided questions I was lost with very little direction, and the direction I did get seemed like it was for something else entirely.

What they should have done was give you two optional courses, one for the guided case study and one for the free case study. From there it can allow the instructor to go into more depth about what you needed to do.

What it actually did was give you two modules in the same week, both with vague checklists, and instructions that don't take the actual data you're working with into account.

For example: the bicycle dataset. They give you YEARS worth of data, going all the way back to 2004, and only want you to use about 12 months worth of it. They want you to use google sheets, R studio, or SQL for this. Well google sheets literally cannot handle that amount of data and you will frequently run out of RAM in R Studio UNLESS you upgrade to a full account, because the dataset is just so large. And uploading it to BigQuery literally required me to upload it to google drive first, and then give it a URI because the files were so massive. But one of the steps REQUIRES you to import it into google sheets.

The issue is that this course doesn't make you do case studies beforehand, it gives you bits and pieces of each part of a case study before throwing you out into sea and making you put all of it together yourself with no rhyme or reason. And it doesn't help you can clearly tell that each course was designed by someone different, which I was willing to put up with until this course assumed so much of the past few courses.

Is this course worth it? Yes, you still learn valuable insights on R, Tableau, SQL, Spreadsheets. But don't expect this to be your sole ticket into becoming a data analyst. Manage your expectations before starting.

Great course overall. Just wish the capstone part was a little more hands-on, and less optional. Helps with accountability.

it is really great course for Data Analyst

Extremely difficult task to undertake if you are a beginner in Data analytics. The 7 preceding courses guide you step by step through the basics, but the skill level required to complete the capstone project is truly overwhelming and leaves you floundering . Hugely dissatisfied ,especially after feeling so motivated and scoring 99% in the previous courses

The resources and guidance through the process of doing a Capstone Project were excellent. However, I was VERY disappointed in the help available to find a job! After I created my profile in the Coursera Job Platform and searched for Data Analyst jobs in Houston, TX, I found exactly zero! You led me to believe that you had a coalition of potential employers ready to consider new Google Data Analytics Certificate holders. That is one of the main reasons that I signed up for this program. Too bad it was not true. I know that there are plenty of analyst jobs available through the usual job search platforms like Indeed. Why are you not tapped into that market? Anyway, overall I don't regret earning the certificate. I am just disappointed at the lack of help leveraging it into a real job offer.

Creating Portfolio is something I was missing even though I have 8 years of work experience as Data Analytics & Visualization Specialist, this remains a big take away for me.

Love the data analytics portfolio project, first time introduced by Google for showcasing case studies and interview preparation.