Project portfolio: Data Scientist

Learn how to build your portfolio fast and easily!

When developing Project Portfolio, we couldn’t omit your favorite topic – data science!

In this article, you’ll find out how to prepare your portfolio – whether you already have some experience or only just started to learn, and several possibilities to join big projects and gain experience.

How to prepare data science portfolio

• Let’s start with planning a portfolio according to what will be interesting for your future employer.
• And if you’re wondering what kind of aa project to chose for your portfolio, look no further than here.
• If you need some more inspiration, check these examples of data science portfolios.

If you haven’t started yet – check this article with five tips on transitioning your career into data science.

Find projects for your portfolio

If you’ve just started your data science journey, and you’re interested in working with R, don’t miss the challenge for beginners run by CrowdAnalytix.

As you know from our last year’s hackathon, inspiring the tech community to tackle socially responsible projects is very important to us. That’s why our suggestions for your portfolio projects will involve mostly initiatives for social good.

If you’re looking for a like-minded community, check FruitPunch AI. The community tries to solve together important social issues implementing machine learning and data science.
If you want to share your skills for good causes while building a portfolio but you’re not so keen on a long-term community, these are the types for you: Driven Data, Omdena, and Zindi Competitions.

What to do next?

If you’re looking for further inspiration, check Data is Beautiful community on Reddit.
And remember to share back your knowledge on StackOverflow.