I corrected a few misspellings

03-CoreGenerativeAITechniques/02-retrieval-augmented-generation.md

@@ -13,7 +13,7 @@ Retrieval Augmented Generation (RAG) is a technique used to augment the response
 There are 2 main phases in a RAG architecture: **Retrieval** and **Generation**.
 
 - **Retrieval**: When the user poses a prompt, the system employs a retrieval mechanism of some sort to gather information from an external knowledge store. The knowledge store could be a vector database or a document, amongst other things.
-- **Generation**: The retrieved information is then used to augment the user's prompt. This AI model processes both the retrieved info and the user's prompt to product an enriched response.
+- **Generation**: The retrieved information is then used to augment the user's prompt. This AI model processes both the retrieved info and the user's prompt to produce an enriched response.
 
 ## Benefits of RAG
 

03-CoreGenerativeAITechniques/03-vision-audio.md

@@ -10,13 +10,13 @@ In this lesson learn how vision AI allows your apps to generate and interpret im
 
 _⬆️Click the image to watch the video⬆️_
 
-Vision-based AI approaches are used to generate and interpret images. This can useful for a wide range of applications, such as image recognition, image generation, and image manipulation. Current models are multimodal, meaning they can accept a variety of inputs, such as text, images, and audio, and generate a variety of outputs. In this case, we are going to focus on image recognition.
+Vision-based AI approaches are used to generate and interpret images. This can be useful for a wide range of applications, such as image recognition, image generation, and image manipulation. Current models are multimodal, meaning they can accept a variety of inputs, such as text, images, and audio, and generate a variety of outputs. In this case, we are going to focus on image recognition.
 
 ### Image recognition with MEAI
 
 Image recognition is more than having the AI model tell you what it thinks is present in an image. You can also ask questions about the image, for example: _How many people are present and is it raining?_
 
-Ok - so we're going to put the model through it's paces and ask it if it can tell us how many red shoes are in the first photo and then have it analyze a receipt that's in German so we know how much to tip.
+Ok - so we're going to put the model through its paces and ask it if it can tell us how many red shoes are in the first photo and then have it analyze a receipt that's in German so we know how much to tip.
 
 ![A composite showing both images the example will use. The first is several runners but only showing their legs. The second is a German restaurant receipt](./images/example-visual-image.png)
 
@@ -143,7 +143,7 @@ You'll need the **Microsoft.CognitiveServices.Speech** NuGet package for this ex
     }
     ```
 
-Using AI to process audio is a bit different than what we have been doing because we are using Azure AI Speech services to do so, but the results of translating spoken audio to text is pretty powerful.
+Using AI to process audio is a bit different than what we have been doing because we are using Azure AI Speech services to do so, but the results of translating spoken audio to text are pretty powerful.
 
 > 🙋 **Need help?**: If you encounter any issues, [open an issue in the repository](https://github.com/microsoft/Generative-AI-for-beginners-dotnet/issues/new).
 
@@ -159,4 +159,4 @@ We have another example that [demonstrates how to perform real-time audio conver
 
 You've learned how to add vision and audio capabilities to your .NET applications, in the next lesson find out how to create AI that has some ability to act autonomously.
 
-👉 [Check out AI Agents](./04-agents.md).
+👉 [Check out AI Agents](./04-agents.md).

03-CoreGenerativeAITechniques/04-agents.md

@@ -45,7 +45,7 @@ Let's see a simple example of this in action!
 
 ### Build a math agent
 
-We'll be building a single purpose agent that acts as a tutor to math students. It's sole purpose in life is to solve and then explain math problems the user asks.
+We'll be building a single purpose agent that acts as a tutor to math students. Its sole purpose in life is to solve and then explain math problems the user asks.
 
 1. To start with, we need to create an `AgentsClient` object that is responsible for managing the connection to Azure, the agent itself, the threads, the messages, and so on.
 
@@ -58,7 +58,7 @@ We'll be building a single purpose agent that acts as a tutor to math students.
 
     ![Screenshot of the project homepage in AI Foundry with the project connection string highlighted in red](./images/project-connection-string.png)
 
-1. Next we want to create the tutor agent. Remeber, it should be focused only on one thing.
+1. Next we want to create the tutor agent. Remember, it should be focused only on one thing.
 
     ```csharp
     Agent tutorAgent = (await client.CreateAgentAsync(
@@ -142,7 +142,7 @@ We'll be building a single purpose agent that acts as a tutor to math students.
 
 > 🙋 **Need help?**: If you encounter any issues, [open an issue in the repository](https://github.com/microsoft/Generative-AI-for-beginners-dotnet/issues/new).
 
-The logical next step is to start to use multiple agents to create an automous system. A next step might be to have an agent that checks to see if the user has a premium account or not.
+The logical next step is to start to use multiple agents to create an autonomous system. A next step might be to have an agent that checks to see if the user has a premium account or not.
 
 ## Summary
 
@@ -168,4 +168,4 @@ Think of agents as AI assistants with agency - they don't just respond, they act
 
 You've come a long way! From learning about simple one and done text completions to building agents!
 
-👉 [In the next lesson see some real-life practical examples](../04-PracticalSamples/readme.md) of using everything together.
+👉 [In the next lesson see some real-life practical examples](../04-PracticalSamples/readme.md) of using everything together.