Build AI-Powered Database Assistants in Python

Published 8/2025
Created by Jim Macaulay
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 30 Lectures ( 1h 24m ) | Size: 563 MB

Master LangChain, PostgreSQL, and Conversational AI to turn Natural Language into SQL-powered insights

What you’ll learn
Fundamentals of AI and LangChain components (LLMs, Chains, Tools, Agents, Memory)
How to connect Python to PostgreSQL and run queries programmatically
Natural language to SQL conversion using LangChain
Designing safe and reliable query pipelines
Enhancing conversations with memory and context
Multi-step reasoning with LangGraph agents
Prompt engineering for schema-aware and secure SQL
Deploying applications with Streamlit (UI) and FastAPI (APIs)

Requirements
Basic Python and SQL knowledge is required

Description
Unlock the power of AI + Databases with this hands-on course on LangChain, PostgreSQL, and Conversational AI.In today’s world, AI is not just about generating text — it’s about connecting intelligent language models with real-world data. This course is designed to take you step by step from the fundamentals of AI to building production-ready AI agents that can query databases, understand natural language, and return user-friendly results.You’ll start by setting up your Python environment and learning the essential AI libraries. Then, you’ll connect to PostgreSQL, run test queries, and integrate your database with LangChain, the powerful framework for LLM applications.Through practical examples and real code, you’ll discover how to:Wrap PostgreSQL with LangChain’s SQLDatabaseChain.Convert natural language questions into SQL queries automatically.Build safer querying pipelines with predefined queries and intent classification.Add memory so your AI can hold conversations with context.Use agents and LangGraph for advanced, multi-step reasoning.Engineer prompts for schema-aware SQL generation and debug queries effectively.Deploy your chatbot with Streamlit and FastAPI for interactive apps and APIs.By the end of this course, you’ll have the skills to design and deploy your own AI-powered database assistant — from a simple chatbot to an advanced agent that reasons about data safely and efficiently