In this book we have learned a workflow for highly reproducible computational research and many of the tools needed to actually do it. Hopefully, if you haven’t already, you will begin using and benefiting from these tools in your own work. Though we’ve covered enough material in this book to get you well on your way, there is still a lot more to learn. With most things computational (possibly most things in general) probably one of the best ways to continue learning is to practice and try new things. Inevitably you will hit walls, but there are almost always solutions that can be found with curiosity and patience. The R and reproducible research community is extremely helpful when it comes to finding and sharing solutions. I highly recommend getting involved in and eventually contributing to this community to get the most out of reproducible research.1