diff --git a/nn-Basics.md b/nn-Basics.md
index c8a65bc..a5f7dd9 100644
--- a/nn-Basics.md
+++ b/nn-Basics.md
@@ -1,17 +1,17 @@
 ## Scope
 * Understand what `torch.nn` is
-* Understand what a Module is
-* Understand how Modules are used to build and train neural networks
-* Understand how to author a Module in PyTorch
-* Understand how to test Modules in PyTorch
+* Understand what a module is
+* Understand how modules are used to build and train neural networks
+* Understand how to author a module in PyTorch
+* Understand how to test modules in PyTorch
 
 ## What is torch.nn?
 `torch.nn` is the component of PyTorch that provides building blocks for neural networks. Its core abstraction is `nn.Module`, which encapsulates stateful computation with learnable parameters. Modules integrate with the [[autograd|Autograd-Basics]] system and are generally trained using optimizers provided in [`torch.optim`](https://pytorch.org/docs/stable/optim.html).
 
-## What is a Module?
+## What is a module?
 Read through the following links:
 * [Introduction to Modules](https://pytorch.org/docs/stable/notes/modules.html)
 * [Neural networks tutorial](https://pytorch.org/tutorials/beginner/blitz/neural_networks_tutorial.html)
 
-## How to author and test a Module in PyTorch
+## How to author and test a module in PyTorch
 Work through the [[lab|Module-Onboarding-Lab]].
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