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Building AI agents for Database

Instructor led course for building AI agents to query RDMS using natural language text and extract contents for RAG.

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4.7

Rating

10 Hrs

Duration

Beginner

Level

10

Assignments

What you'll learn

How to interact with RDMS using natural language
How to extract context from RDMS for RAG based application
How to expand Agent’s scope to add CRUD operations like insert and update

Who should take this course

Ideal for anyone with python programming and AI agent knowledge
It is recommended to do the “AI Agent for beginners” training before joining this course

Skills you'll gain

AI agents
LLM
SQL
RAG
RDMS
Streamlit
Postgress DB

Course contents

What they do
Technology stack required

Set up Postgress DB

Set up LangChain and LLM

Get tables and schemas
Create the SQL query
Validate and run the SQL query

Creating demo web UI in python streamlit

Calculate the Agents accuracy metrics

Developing LLM powered Chat Bot for customer support

Here we will built a context-enabled LLM-based chatbot that will answer all customer queries related to product and services.

Extracting structured output from documents using LLM

In this workshop a PDF based Q&A solution will be devloped from scratch, where user can ask question to PDF and get answers.

Applying GraphRAG in healthcare diagnostics

This workshop focuses on how to enhances the performance of RAG LLM by adding external knowledge base.