add folders based on outline

Author: crpietschmann

.gitignore

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+
+.DS_Store

01_Overview_Cosmos_DB/README.md

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+# Overview of Azure Cosmos DB (high-level with links to docs for more information)

02_Overview_Azure_OpenAI/README.md

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+# Overview of Azure OpenAI

03_Overview_AI_Concepts/README.md

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+# Overview of the following concepts (summaries with reference links):
+
+- Large Language Models (LLM)
+- Standard patterns (RAG, CoT, ReAct, etc.)
+- Vectorization and vector search
+  - What are you trying to solve with finding relevant data through vector search?
+- Prompt engineering

04_Provision_Azure_Resources/README.md

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+# Provision Azure resources (Azure Cosmos DB workspace, Azure OpenAI, etc.)
+
+- Have deployment scripts
+- Walk through the deployed environment

05_Create_First_Cosmos_DB_Project/README.md

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+# Create your first Cosmos DB project (console app (Jupyter notebook?))
+
+- How to use the Cosmos DB SDK
+- How to develop locally

06_Explore_OpenAI_models/README.md

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+# Explore the Azure OpenAI models and endpoints (console app)
+
+- Selecting an LLM
+- Explore and use models from code
+    - Completions
+    - Chat completions
+- Do I use an out-of-the-box model or a fine-tuned model?
+- Use the embeddings model to vectorize data

07_Vector_Search_Cosmos_DB/README.md

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+# Use vector search on embeddings in Azure Cosmos DB for MongoDB vCore (console app)
+
+- What problem does vector-based searching solve?
+- Create a vector index
+- Store vectors
+    - Load a text file (policy, FAQ, etc.)
+- Perform a vector search on the index

08_Load_Data/README.md

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+# Add document collection to MongoDB and load data (console app)
+
+- Manually load data and ask questions about it
+- Run data generator to load sample data
+    - We need to find a good data set

09_Chatbot_API/README.md

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+# Complete the chatbot API
+
+- Select an orchestration framework
+- Update the starter project to implement the Azure Cosmos DB for MongoDB database for chat history
+- Implement Azure OpenAI for embeddings and completions