fixes

Author: alexwolfmsft

articles/search/includes/quickstarts/search-get-started-vector-dotnet.md

@@ -44,11 +44,11 @@ This quickstart uses `DefaultAzureCredential`, which simplifies authentication i
 
    This repo has .NET code examples for several articles each in a separate subfolder.
 
-1. Open the subfolder `quickstart-Vector-Search` in Visual Studio Code.
+1. Open the subfolder `quickstart-Vector-Search` in Visual Studio Code, or double click the `.sln` file to opn the solution in Visual Studio.
 
-1. In Visual Studio Code, open the `appsettings.json` files in the `VectorSearchExamples` and `VectorSearchCreateIndexUploadDocs` folders. Update the following values: 
+1. Open the `appsettings.json` files in the `VectorSearchExamples` and `VectorSearchCreatePopulateIndex` folders. Update the following values: 
 
-   - `AZURE_SEARCH_ENDPOINT`: You can find the url in the [Azure portal](https://portal.azure.com). Go to your Azure AI Search service, on the **Overview** page, look for the URL field. An example endpoint might look like `https://mydemo.search.windows.net`. 
+   - `AZURE_SEARCH_ENDPOINT`: Find the url of your Azure AI Search service in the [Azure portal](https://portal.azure.com). On the **Overview** page of your search resource, look for the URL field. An example endpoint might look like `https://mydemo.search.windows.net`. 
    - `AZURE_SEARCH_INDEX_NAME`: Leave the default value provided in the file or enter your own index name.
 
 ## Create the vector index and upload documents
@@ -89,7 +89,7 @@ Key takeaways:
 
     - **Data ingestion**: `UploadDocuments()`, `MergeDocuments()`, `DeleteDocuments()`
     - **Search operations**: `Search()`, `Autocomplete()`, `Suggest()`
-    - **Index management operations**: `CreateOrUpdateIndex`
+    - **Index management operations**: `CreateOrUpdateIndex()`
 
 - Vector fields contain floating point values. The dimensions attribute has a minimum of 2 and a maximum of 4096 floating point values each. This size of embeddings generated by the Azure OpenAI **text-embedding-3-small** model for this quickstart is 1536.
 
@@ -303,7 +303,7 @@ The hybrid query with semantic ranking is filtered to show only the hotels withi
 
 1. In the `Program.cs` file of the `VectorSearchExamples` folder, uncomment the method call `SearchExamples.SearchHybridVectoryAndSemantic(searchClient, vectorizedResult);`. This method executes the following search function in the `SearchExamples.cs` class:
 
-    :::code language="csharp" source="~/azure-search-dotnet-samples/quickstart-vector-search/vectorsearchexamples/SearchExamples.cs" id="SearchHybridVectoryAndSemantic":::
+    :::code language="csharp" source="~/azure-search-dotnet-samples/quickstart-vector-search/vectorsearchexamples/SearchExamples.cs" id="SearchHybridVectorAndSemantic":::
 
 1.  Run the project again, and the status of each document is printed below it: