A Guide To Getting Data Science Projects Ideas

A Guide To Getting Data Science Projects Ideas

How to come up with self-study, portfolio or business ideas. From someone with too many. When writing about learning or breaking into data science, I always advise building projects.

When writing about learning or breaking into data science, I always advise building projects.

It is the best way to learn as well as showcase your skills.

But I often get messages from readers asking, “How exactly do I come up with ideas for my projects?”

Any seasoned entrepreneur or engineer will tell you they have too many ideas. But it’s not always easy when you’re starting out.

So here’s a few ways I’ve personally come up with ideas.


Attend networking events and talk to people

Most people are surprisingly willing to share their own ideas. You just have to ask.

My default question at networking events is, “What are you working on or trying to solve?”

Last week at a virtual event, every single non-technical person I talked to shared a use-case for ML that they wanted to build.

Now don’t steal anyone’s idea. But if you’re already dedicating hours to learn data science, consider helping someone for free. You’ll get experience to put on your resume and a connection that may be useful in your career.

Successful people are happy to share ideas. They understand there are an infinite number of problems to solve in the world, and sharing isn’t a zero-sum game.


Use your hobbies and interests to generate ideas

Many great ideas have come from merging expertise across different domains.

For example, Geoffrey Hinton, the inventor of neural networks, had a background in psychology from which he drew many early ideas about artificial intelligence.

How can you apply this to your own interests?

Personally, I love my dog, badminton, and cooking. I’m also aware of the general topics under the machine learning umbrella. So I’ll try to match a type of ML with each of my hobbies to generate an idea.

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