You probably know by now, that one of the best ways to learn data analytics is by building projects.

The coolest projects I’ve seen are ones that are personal to the author in their personal life.

Maybe it’s analyzing your phone screentime, or analyzing your spending habits—anything that helps you make smarter decisions with data.

When you make it personal, you’re more likely to actually finish the projects AND impress a hiring manager.

Here are 7 of my favorite personal data projects 👇

(and yes, I included a lot of my own; it’s my newsletter I can do what I want to 🤣)

1. “I Used Data Science to UNCOVER McDonald’s Healthiest Meal” by Me

2. “I Analyzed My Finance With Local LLMs” by Thu Hien Vu

3. “Tableau Visualization with Your Own LinkedIn Data” by Me

4. “I used Python to Count my Bike Jumps!” by Luke Barousse

5. “Fitness Dashboard in Power BI” by Me

6. “Data Scientists VS NFT Scam” by Ken Jee & Me

7. “Beginner NLP Data Science Project with Python” by Me

I interviewed Thu this week on my podcast and we talked about some of the cool projects she’s been making.

You can watch the full thing here

Hopefully, this helps you understand why projects are so important! And why they're a big focus of The Accelerator.

In The Accelerator program, after building 9+ industry-relevant projects, you'll do a capstone project with our guidance. I encourage you to build a personal project for your capstone.

Click here to learn more.

Personal Projects are fun.

Personal Projects are useful.

Personal Projects will help you.

Build more personal projects.