Google Data Analytics Certificate Course 1 Review: What You'll Actually Learn

Google Data Analytics Certificate Course 1 Review

I've completed the first course in the Google Data Analytics Certificate: Foundations: Data, Data, Everywhere (sounds like it should be a song).

At the time of recording, there were 28,500 people enrolled. One week later: 43,900. That's 15,000 new enrollments in a week. This thing is getting attention.

How I Approached It

Google offers a diagnostic quiz. If you pass with 80% or higher, you can take the "fast track"—essentially, take the tests and circle back on content as needed.

I passed. But here's the thing: even though I've been an analyst since 2004, there's always something to learn. Especially with foundations.

Just because you've built on a foundation over time doesn't mean there aren't cracks that need reinforcing.

Course Structure

The course is broken into 5 weeks:

Week 1: Introducing Data Analytics

What does a junior analyst do?
Why do we analyze?
Where is data? What is data?

This is baseline foundation building. Super high level, but necessary.

Week 2: Thinking Analytically

They've got a whole section dedicated to analytical thinking and questioning techniques.

Half of an analyst's job (maybe more) is asking smart questions. Not writing code—asking questions, getting feedback, then asking smarter questions.

I love that they dedicated an entire week to this.

Week 3: Exploring the World of Data

Data fundamentals
The data life cycle
Outlining the analysis process

They're setting definitions and standards. Even if the terminology doesn't match exactly what I use, having common language matters.

Week 4: Setting Up a Data Toolbox

Spreadsheets (they use Google Sheets)
SQL basics (very basic—just SELECT FROM WHERE)
Visualization concepts

This isn't deep technical training. It's exposure to what these tools are and what they're good for.

Week 5: Discovering Data Career Possibilities

Learning about different analyst roles
Hearing from Google employees about their paths
Understanding fairness and bias in data

What They Did Really Well

Multiple Formats

This isn't "watch a video and click through." There are:

Videos
Readings (basically cliff notes of the videos)
Practice exercises
Quizzes
Discussion prompts

Real Engagement

They push you to participate in forums. There's community discussion. It gives some semblance of a classroom environment.

Different Voices

They brought in multiple Google employees to share their perspectives and stories. It makes the content more approachable.

Pop-Up Questions

During videos, questions randomly appear. It keeps you engaged and prevents you from just hitting play and walking away.

My Honest Assessment

The questions I missed on quizzes were always definitional. Things I wanted to argue about.

But I get it. You can't build a foundation unless there's structure and consistency. They're setting definitions so everyone speaks the same language going forward.

For beginners: This is absolutely a 5-star foundational course.

For experienced analysts: Use the fast track. Take the tests, then circle back on anything interesting. Don't rate it poorly just because you didn't learn anything new—understand the context of who it's for.

The Validation

A lot of what they teach aligns with what I've been saying for years. That made me feel good—it validates that my real-world experience matches what Google considers best practices.

If you're considering the Google Data Analytics Certificate, the first course does exactly what a foundations course should do: set the table for everything that comes next.

Common Questions About Google Data Analytics Course 1

Q: Can I skip Course 1 if I already know what data analytics is?

Take the diagnostic quiz. If you score 80%+, use the fast track—take the final assessment and move on. But even experienced analysts might find value in the analytical thinking module.

Q: How long does Course 1 actually take?

Google estimates 20 hours. If you're new to analytics, budget that full time. If you're experienced and fast-tracking, you can finish in 2-3 hours.

Q: Is Course 1 worth paying for or should I audit?

If you're planning to complete the full certificate, pay for it. You need the graded assignments and certificate credit. If you're just curious, audit it for free.