First Thoughts on Google’s Data Analytics Professional Certificate on Coursera!

Hey JAMers!

Today I’m diving into my experience of up-leveling my skill set with Google’s Data Analytics Professional Certificate.

Just as a quick disclaimer: this post is in no way sponsored and all thoughts and opinions are my own.

Okay, so why the Data Analytics Certificate?

Well lately I’ve been noticing the rise in tech jobs, but also the rise in the need for having tech skills in any industry. Currently, I’m a public librarian by trade. Still even in my current position, the pivot to a virtual setting during COVID-19 illuminated the need to have a better understanding of the tech we were using and also the data being collected and analyzed.

How am I supposed to accurately analyze what virtual programs were working and which ones weren’t? How can I tell if our virtual programming or marketing were effective or not? How do I compare data from this year to previous years with the transition from in-person to virtual programs and services? How did the library being closed affect circulation numbers, especially when it comes to weeding our collection?

You get the picture.

Data was everywhere, but I wasn’t affectively utilizing it. So as a lifelong learner, I decided to do what I do best and dig into learning more about data and data science.

I chose the Data Analytics certificate from Google because I heard great things about it on some podcasts I had been listening to and because this type of work interested me. I already had some experience utilizing SQL during my database management class for my Masters in Library Science and I’ve been using spreadsheets a lot for work. Still, I don’t have a massive technical background and this certificate’s description mentions that it’s for beginners and for those with no technical skills. So, this certificate program seemed like a good fit.

Certificate Breakdown

• The certificate is earned via Coursera.org
• The certificate program is available via a monthly subscription of $39.
• Its projected completion is within 6 months
• The certificate program is broken down into 8 courses with each course containing 4-6 weeks of work.
  • Course 1: Foundations – Data, Data, Everywhere
  • Course 2: Ask Questions to Make Data-Driven Decisions
  • Course 3: Prepare Data for Exploration
  • Course 4: Process Data from Dirty to Clean
  • Course 5: Analyze Data to Answer Questions
  • Course 6: Share Data through the Art of Visualization
  • Course 7: Data Analysis with R Programming
  • Course 8: Google Data Analytics Capstone – Complete a Case Study
• The course is taught with a mix of videos, readings, hands-on activities, in-video questions, content reflection activities, discussion posts, quizzes, weekly challenge tests and a final course test.

Currently I’m halfway through the certificate program — finishing up Course 4.

Below are some Pro’s and Con’s I have about the certificate program so far.

PRO’s

• While the course has pre-set deadlines, it’s self-paced so you can finish ahead or reset deadlines as needed.
• Each quiz & test can be completed 3 times within a 24-hour period and the course will keep your highest grade.
• The trainers/teachers change in each course and they illustrate a diverse range of job roles, backgrounds and experiences.
• Each course has brought in other Google employees to touch on certain topics for another perspective.
• The content is delivered in a way that assumes learners are coming from a non-tech background. So I’ve found it easy to follow and understand.
• Each piece of content (outside of tests and quizzes) is generally no longer than 10 minutes.
• Each video contains a ‘transcript’ tab to follow along with and to highlight and create into saved notes. This notes feature is also available with the readings.
  • As a heads up, I don’t use their ‘Notes’ feature. But I do rely heavily on the transcript tab when taking my notes. I use Notion for note-taking and course tracking.
• The course’s hands-on activities usually are provided via Google Templates you can save to your Google Drive, but they also provide a downloadable version if you’re using Microsoft Excel or don’t have a Google account.
• The course provides your status for percentage completed and how many hours or minutes you still have left to complete in a week and within a course.
• So far, the program has introduced me to tools and resources I haven’t heard of before. It has also linked to additional readings and articles.
• The program structure – in terms of course sequence – is set up in a logical way that flows.
• If you are just taking this course as a refresher or if you have a tech background, there is the option to test out of some of the beginning courses.

CON’s

I don’t have a lot of cons so far to be honest. I’m really enjoying this course and so I don’t want to be dishonest and nitpick it just to come up with a long list of cons. So below are two things that I think are somewhat cons or things to be aware of anyway.

• The course doesn’t go too in-depth on each topic.
  • Basically, this is a certificate course and not a bootcamp. The primary objective is to give you a solid foundation you can use to build more learning upon or to give you a slight edge into transitioning into a tech role. So this isn’t a technical CON of the certificate, but if you’re looking for a really in-depth program, maybe do a bootcamp or multiple certificate programs.
    • I’m planning on trying to do the IBM one that Coursera offers as well and basically any other trainings I can do.
  • So there isn’t an in-depth look or practice of SQL outside of the basic retrieval commands.
  • There was a great insight into commonly used excel functions, but I’m still planning to do more in-depth advanced excel training.
• This certificate program only touches on R Programming.
  • I’ve read and listened to podcasts that mention Python a lot. There’s a debate about which language to learn, but I personally think it’s okay if you know one as you will be able to learn the other one on the job or quickly enough to transition, especially if you’re good with programming languages or are a quick learner in general.
  • I plan on trying to learn both if I can.

Tips & Tricks

• Set aside time and really work on it. It will go quickly if you dedicate time to it. It’s a 6-month certificate program, but you can definitely get it done before that which will save you money.
• Utilize some kind of note taking system.
  • I use Notion.so for note taking. I like to do a split screen and listen or read and then take notes on the other screen. You can also use a traditional notebook or try out Coursera’s note system.
• USE THE TRANSCRIPT TAB!
  • If you’re not taking notes this might not apply to you, but I like to read the transcript and take notes from the transcript and then watch the video.
  • Sometimes the videos go by really quick, I find utilizing the transcript pages allows me to get all the content and really digest the information being shared. Also, this prevents me from starting and pausing the video every time I want to write a note down.
• Follow Along with the Instructor.
  • Within certain courses and lessons you’ll be offered the opportunity to “follow along with the instructor.” I highly recommend this as you’ll be able to practice utilizing the formulas, preparing the data, cleaning the data, etc.
  • I learn best by doing and this gives me the opportunity to “do.”
• You Get What You Put In!
  • Like any class, course, lesson, etc. it’s what you put into it that will determine what you take away from it. If you just breeze through without putting in the work then you’ll probably not learn as much as you could or be able to showcase in an interview or on your resume that you know what to do for this type of role. I know not everyone considers themselves a “student” or a “good learner,” but if this is something you want to do as a career then I’d try to do what you can to get the most out of this program.

I hope this (very long, hah!) post gives you a little insight into the Google Data Analytics Professional Certificate on Coursera.org. If you have any questions feel free to reach out to me here, on Twitter or Instagram @JustNicoleLynn or email me at justaddmore (@) gmail.com

Happy Learning!

xx Nicole Lynn