15. Conclusion

Congratulations on getting through this book! We covered a lot, and it wasn’t easy, but we hope you are proud of yourself for working through it, and as excited to put your newfound data science skills to use in the world to tackle interesting, important, and exciting problems as we are to see you do it.

In case it’s not obvious, we think data science is pretty great. It’s interdisciplinary, it’s challenging, it requires different kinds of skills, it’s rewarding, and it’s fun. It’s also, as we discussed at the opening of the book, increasingly becoming required knowledge for participation in and contribution to the world. There are very few fields left that are not at least in some way touched or influenced by data science, however indirectly.

But we also want to acknowledge it’s not easy. In this book we’ve challenged you to grapple with concepts from research design, causal inference, computer programming, statistics, mathematics, measurement, machine learning, linguistics, ethics, and more – and none of these areas on their own are a walk in the park. In designing this book and the course, it’s of course always a debate between exploration and exploitation – how deep to go in one area, versus how many different areas of data science to cover. We’ve ultimately taken something of a “yes, and” approach: while there are definitely entire courses out there on pretty much every chapter of this book alone, we also challenged you to rigorous applications and implementations of these concepts, and if you’ve gotten this far, you more than rose to the occasion.

15.1. Welcome to the first day of the rest of your life!

In sum: We hope this book provided a strong foundation for you in both building your data science skills, as well as sparking your curiosity to continue, and to roll up your sleeves and start conducting your own ethical and rigorous data science research right away with both fearlessness and humility. Do tell us what you get up to – we’d love to learn from and celebrate your discoveries.

Most of all, thank you for joining us on this journey to get everyone involved in data science, and don’t forget: data doesn’t say anything; we say things about data.