What can you do now?

If you have finished this first part early, please see the list below for some suggestions for how to best spend your time before accessing the next part of the content!

### Write up a blog post or record a YouTube video explaining what you have learned.

The best way to make sure you have learned something (and deepen your understanding) is to explain it to somebody else!

### Revisit the coding exercises, and analyze the effects of the various hyperparameters.

You can either work in the provided Udacity Workspaces or download the exercises from the DRLND GitHub repository.

### Explore the various applications of reinforcement learning.

If you have an application area in mind, try reading a couple of research papers (or blog posts) that discuss how RL is applied to your topic of interest.

### Review neural networks, and learn PyTorch.

For this course, you are expected to know how neural networks train through backpropagation. If you’d like to review this material, we have prepared two lessons that appear in the extracurricular content.

In the extracurricular content, you will also find a lesson that introduces PyTorch. We will use PyTorch throughout this program. If you are unfamiliar with PyTorch and have time now, you're encouraged to check out the lesson. (If not, don't worry - you'll also have time in the second part of the program to learn PyTorch.)