Google Data Analytics Certificate: 10-week study plan

I put off taking the Google data analytics certificate because I thought it would take forever… in this article I’ll share what I learned so you can plan your time.

So, how long does Google data analytics certificate take?

First, we should acknowledge that the course is advertised as around 140+ hours for the mandatory modules, but my experience and other students’ experience show that completion time varies.

How long it’s going to take you is determined by:

• Your previous data analytics experience (I had none)
• Your willingness to put the time in
• How comfortable you feel with the tools, and how quickly you pick up the concepts
• Your learning style and preferences – people who take a lot of personal notes are going to probably learn more comprehensively, but it will take longer.

Having said all of that, the most important factor is your motivation: why are you doing this course? If it’s simply to tick a box, you can scan through the materials. If you are doing it because you really want to get an analytics job, you’ll need to truly learn and therefore spend more time on the concepts and assignments.

Not sure if the course is right for you? Read my full Google Data Analytics Certificate review.

Google Data Analytics Certificate: Time estimates from Coursera

The published Google data analytics time commitment recommendation is that you should spend 10 hours per week on learning which means it will take you around 6 months to finish the materials.

The timeframes given by Google (and Coursera) for each module are:

1. Foundations: data, data, everywhere: 12 hours
2. Ask questions to make data-driven decisions: 15 hours
3. Prepare data for exploration: 19 hours
4. Process data from dirty to clean: 20 hours
5. Analyze data to answer questions: 26 hours
6. Share data through the art of visualization: 18 hours
7. Data analysis with R programming: 31 hours
8. Capstone project (case study): 11 hours
9. Accelerate your job search with AI: 6 hours

Don’t worry – you can complete it much faster. Lots of students report completing it in 2-3 months, and I read of one student who completed it in 14 days. If you can spare a couple of evenings a week or a full weekend day, you can get through the material sooner.

That will literally pay, because Coursera charges you monthly for access to the materials. The faster you complete it, the sooner you can stop paying for it!

Obviously, the time to complete the certificate depends on how much effort you put in. I found that when I stopped studying for a few days, I actually ended up stopping for a lot longer as I got out of the habit. The timeline for completion really does depend on you.

Realistic completion time for the Google Data Analytics course

I found that I was much faster with the Foundations module than any of the others because it covers ‘corporate’ stuff that I found easy to pick up. I got through the first module of that in a couple of hours one Saturday afternoon, and that included going through all the ‘general’ course readiness introductory pieces as well.

The data analysis with R module includes learning new tools, so the recommendation is right that it will take longer than any of the others. How long it takes also depends on how much past experience you have with data analysis, your learning preferences and styles, and whether you are doing it ‘seriously’ or just scanning through the materials for the certificate.

So, assuming you are doing it seriously, and have a full-time job like me, here’s how you can plan out your personal time to complete the certificate.

10-Week Google Data Analytics study plan

Here’s a Google Data Analytics study plan that you can use as a starting point for your own learning.

• Week 1: Foundations
• Week 2: Ask questions
• Week 3: Prepare data
• Weeks 4-5: Process data
• Weeks 6-7: Analyze data
• Week 8: Share data with visualization
• Weeks 9-10: R programming

This Coursera data analytics weekly schedule doesn’t include time recommendations for the Capstone or the AI job search courses as these are optional. If you do want to do them, the Capstone could take 2-4 weeks. The AI job search course you can complete in an afternoon.

Each course has a different number of modules.

Foundations has 4 modules. You’ll get through this course the quickest and it gives you a chance to get into the studying habit. My advice is to blitz this as fast as possible, especially if you have ‘corporate’ experience.

Ask questions has 4 modules, with module 4 being one on stakeholder relationships so that’s a relatively ‘light’ module if you’ve worked in corporate jobs. No hard concepts there.

Prepare data has 5 modules. Module 4 and 5 are short, but the database essentials module is time-consuming.

Process data is 6 modules. Module 5 is optional as it’s about adding data to your resume – which may or may not be relevant. You can always come back and do it later. Not completing that module won’t affect your pass mark for the course. The final module is a course wrap up which you can scan through quickly.

Analyze data is 4 modules but this is a sizeable course so it’s worth allowing a couple of weeks. If you do it faster, great.

Sharing data is 4 modules, with module 4 being about creating slide presentations. If you are already experienced at using slides and building out stories in presentation format, you will be able to get through this one quite quickly.

R programming is 5 modules. There is a lot of new things in here. While the course builds on what you have learned in other courses, you’ll be programming in RStudio, learning R Markdown, creating visualizations and exporting them.

If you already have R experience or pick up this kind of tool quickly, you might be able to do it faster, but it is not something I have previous experience of. This is where I’m going to need to spend more time, and you might too, especially if you want to then evidence to employers you can do the job, rather than just knowing about the job.

How to finish the Google Data Analytics Certificate faster

OK, let me share some tips for how to complete the Professional Certificate faster. However, be aware that whizzing through the material does not equal learning!

If you want to recall the concepts and be able to talk about it at an interview, learn at your own pace.

• Watch videos at 1.5x or 1.75x speed.
• Read the transcripts instead of watching the videos at all (skip to the end of the video with the scrub bar to mark it as complete)
• Focus more time on hands-on labs and assignments – this is the really valuable stuff
• Batch small modules into study sprints
• Use the mobile app for flexibility so you can watch videos on the move
• Complete your data journal as you go – it does help.

You’ll also complete it faster if you don’t do the Capstone or the AI job search module. Having said that, you get the certificate whether you do those courses or not, so it won’t make it faster really – it will just feel faster!

Is the Google Data Analytics certificate worth the time?

Even part-time study makes progress. I watch Coursera videos while at the gym (which is not often!!) or while having breakfast. You can fit them in as they aren’t long.

You’ll be learning new skills throughout the course, and you can put those into practice immediately in your job. You don’t have to wait until you complete the whole certificate before you use them or talk to your employer about your career preferences.

Read next: What employers think about job seekers with Google Professional Certificates

I asked a number of employers about whether they rate this training and the results were broadly positive. Jared Bauman, CEO of digital agency 201 Creative, LLC, summed it up.

“We’ve interviewed and hired candidates who listed Google Professional Certificates, particularly in Digital Marketing and Project Management,” he said. “While the certificate alone is not enough to guarantee a hire, it signals that the candidate has taken initiative and completed focused, relevant training. It often helps them stand out in a crowded applicant pool, especially when they lack formal experience. We view it as a strong supplemental credential.”

Want to start today?

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