Update README.md

Author: kyleoconnell-NIH

GoogleCloud/README.md

@@ -1,15 +1,15 @@
 ## Contents
 
 + [Getting Started](#getting-started)
-+ [Creating a notebook instance with R kernel in Google cloud](#creating-a-notebook-instance-with-r-kernel-in-google-cloud)
++ [Creating a notebook instance with R kernel in Google Cloud](#creating-a-notebook-instance-with-r-kernel-in-google-cloud)
 + [Creating Google Cloud Storage Buckets](#creating-google-cloud-storage-buckets)
 + [Google Cloud Architecture](#google-cloud-architecture)
 
 ## Getting Started
 Each learning submodule will be organized in an R Jupyter notebook with step-by-step hands-on practice with R command line to install necessary tools, obtain data, perform analyses, visualize and interpret the results. The notebook will be executed in the Google Cloud environment. Therefore, the first step is to set up a notebook instance in VertexAI.
 
 
-## Creating a notebook instance with R kernel in Google cloud
+## Creating a notebook instance with R kernel in Google Cloud
 
 Follow the steps highlighted in part two (2. Spin up Instance from a Container) of [here](https://github.com/NIGMS/NIGMS-Sandbox/blob/main/docs/HowToCreateVertexAINotebooks.md) to create a new notebook instance in Vertex AI. Follow steps 1-8, in step 5 select region us-east4 (Northern Virgina) and be especially careful to use custom container `us-east4-docker.pkg.dev/nih-cl-shared-resources/nigms-sandbox/nigms-vertex-r` in step 6 under the Docker container image prompt. In step 7 under the Machine type tab, select n1-standard-4 from the dropdown box. In step 8, be carefull to **Enable Idle Shutdown**. After creating the notebook you can click on **OPEN JUPYTERLAB**.
 
@@ -77,4 +77,4 @@ User can either upload the Notebooks to the VertexAI workbench or clone from the
 the code directly in the Notebook. In our learning course, the submodule 01 will download data from the public repository (e.g., GEO database)
 for preprocessing and save the processed data to a local file in VertexAI workbench and to the user's Google Cloud Storage Bucket. The output
 of the submodule 01 will be used as inputs for all other submodules. The outputs of the submodules 02, 03, and 04 will be saved to 
-local repository in VertexAI workbench and the code to copy them to the user's cloud bucket is also included.
+local repository in VertexAI workbench and the code to copy them to the user's cloud bucket is also included.