Library / Artificial Intelligence
Spring AI Text-to-SQL: Turning Questions into SQL with LLMs
On Udemy
About this course
Text-to-SQL is one of the most powerful real-world use cases for Large Language Models. The idea is simple: a user asks a question in plain English, and the system generates and executes SQL automatically.> Doing this with ChatGPT is easy.> Doing this safely and correctly inside a backend system is not.
This course teaches you how to build a complete, production-style Text-to-SQL system using Spring AI, Spring Boot, and PostgreSQL, with clear architecture, strong backend control, and zero reliance on “AI magic”.You will not build a chatbot. You will not build a dashboard. You will build a backend system that you could confidently use at work.
Includes professionally prepared subtitles in Spanish, Portuguese (Brazil), Japanese, and Chinese.
Includes free 90-day access to IntelliJ IDEA Ultimate for a professional development experience.
What makes this course different
Most AI + SQL demos you see online follow this pattern:
- User question → LLM → SQL → Database
This course shows why that is dangerous, and how to design the system properly:
- User question → Spring Boot backend → LLM → SQL validation → Database
- The LLM suggests.
- The backend controls everything.
- What you will build
Throughout the course, you will work on a single Spring Boot project that evolves module by module. Instead of toy examples, you will use a realistic company database (employees, projects, customers, orders, invoices, payments) so queries feel like real systems.
You will build:
- A Text-to-SQL API using Spring AISchema-aware prompt design to improve SQL accuracy
- Dynamic schema discovery from PostgreSQL at runtimeAST-based SQL validation to block unsafe queries
- Table and column validation using real schema<
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Udemy: 2026-09-27 · Coursera: 2026-09-27
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