Creating your first project

Last updated on July 7, 2023 at 11:56 PM

In this post, we’ll cover how to make your first project and tell an effective story using data. In the end, you’ll have a project that will help demonstrate the first two skills: the ability to communicate and the ability to reason about data.

Storytelling with data

Data science is fundamentally about communication. You’ll discover some insight in the data, then figure out an effective way to communicate that insight to others, then sell them on the course of action you propose. One of the most critical skills in data science is being able to tell an effective story using data. An effective story can make your insights much more compelling, and help others understand your ideas.

A story in the data science context is a narrative around what you found, how you found it, and what it means. An example might be the discovery that your company’s revenue has dropped 20% in the last year. It’s not enough to just state that fact — you’ll have to communicate why revenue dropped, and how to potentially fix it.

The main components of storytelling with data are:

Understanding and setting the context
Exploring multiple angles
Using compelling visualizations
Using varied data sources
Having a consistent narrative

Complete Your First Guided Project: Prison Break

If you haven't done one before, today is a great day to complete your very first data science project. Don't worry, anyone can complete this free guided project. You'll learn the basics of Jupyter notebook and work with a dataset on helicopter prison breaks.

We'll answer the following questions:

In which year did the most attempts at breaking out of prison with a helicopter occur?
In which countries do the most attempted helicopter prison escapes occur?

Complete the project here >> then keep reading!

Choosing a topic for your data science project

Once you've completed your first guided project it is time to think about starting one of your own. You'll want the topic to be something you’re interested in and are motivated to explore. It’s very obvious when people are making projects just to make them, and when people are making projects because they’re genuinely interested in exploring the data. It’s worth spending extra time on this step, so ensure that you find something you’re actually interested in.

A good way to find a topic is to browse different datasets and see what looks interesting. Here are some good sites to start with:

Data.gov — contains government data.
/r/datasets — a subreddit that has hundreds of interesting datasets.
Awesome datasets — a list of datasets, hosted on Github.

In real-world data science, you often won’t find a nice single dataset that you can browse. You might have to aggregate several sources or do a good amount of data cleaning. If a topic is interesting to you, it’s worth doing the same here, so you can show off your skills better.

More in this series: