https://github.com/thaiebu/building-your-own-database-agent-course

This course, created in partnership with Microsoft and taught by Adrian Gonzalez Sanchez, focuses on developing an AI agent that interacts with databases using natural language. This simplifies the process of querying and extracting insights without needing advanced SQL knowledge.
https://github.com/thaiebu/building-your-own-database-agent-course

Last synced: 25 days ago
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This course, created in partnership with Microsoft and taught by Adrian Gonzalez Sanchez, focuses on developing an AI agent that interacts with databases using natural language. This simplifies the process of querying and extracting insights without needing advanced SQL knowledge.

• Host: GitHub
• URL: https://github.com/thaiebu/building-your-own-database-agent-course
• Owner: Thaiebu
• Created: 2024-07-20T15:30:07.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-07-20T15:33:05.000Z (6 months ago)
• Last Synced: 2024-07-20T16:47:17.248Z (6 months ago)
• Language: Jupyter Notebook
• Size: 21.5 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.md

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README

        
I'm excited to share my recent learning experience from the **[Building Your Own Database Agent](https://coursera.org)** course! This course, created in partnership with Microsoft and taught by **Adrian Gonzalez Sanchez**, focuses on developing an AI agent that interacts with databases using natural language. This simplifies the process of querying and extracting insights without needing advanced SQL knowledge.

Here's what I learned:

1. Customizing AI agents with Azure OpenAI Service, focusing on Retrieval Augmented Generation (RAG).

2. Loading data from CSV files and performing natural language queries using Azure OpenAI Service.

3. Building a DB agent that translates natural language to SQL code.

4. Using Azure OpenAI Service's function calling feature to send queries to databases, improving efficiency and security.

5. Working with the Assistants API and testing it with function calling and code interpreter features.

By the end of the course, I gained practical experience in implementing these systems in my projects, enabling efficient and accessible data interaction and analysis. I have attached the completed exercises related to this course.