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Build AI Application with Spring boot, Ollama and MCP
Published 5/2026
Created by Ravi Kumar Singh
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 17 Lectures ( 4h 35m ) | Size: 2.22 GB
Learn Spring AI, LLMs, Llama, Tool calling, AI Agents and enterprise AI Architecture from scratch
What you'll learn
Build AI-powered backend applications using Spring Boot and Spring AI from scratch.
Integrate and run local LLM models like Llama 3 using Ollama for real-world AI workflows.
Implement Prompt Engineering, Tool Calling, AI Agents, conversational memory, and enterprise AI orchestration concepts.
Design and develop production-style AI architecture with REST APIs, database integration, and scalable enterprise patterns.Requirements
Java
Spring boot working knowledge
web development basic ideaDescription
Have you ever wondered how ᑕᕼᗩTGᑭT-like applications are built using Java and Spring Boot?
Do you want to learn how modern AI applications integrate with Large Language Models using the Spring ecosystem?
If yes, then this project is the perfect starting point for you.
In this hands-on project, you will build a production-ready AI-powered backend application using Spring Boot, Spring AI, Ollama, Postman, and H2 Database while understanding the complete AI application development workflow from scratch. This project is specially designed for Java developers who want to enter the world of Generative AI using technologies they already know and love. This course outlines are like below. I have covered each and cry prerequisite knowledge in details.
Section 1: Introduction
Introduction and welcome to course
What we will build
About me and other course
resourcesSection 2: From Traditional Software to AI Engineer with Spring boot
Welcome to AI Engineering Journey
Evolution of Software Engineering
Architecture of Modern AI Application
LLM API and AI Model communicationSection 3: Prompt Engineering fundamental
Prompt Engineering Fundamentals
Context Engineering in AI SystemSection 4: Project Development
Introduction to Spring AI
Project Structure
Create Employee Service
Create MCP Server
Create Chat Client
Bug FixSection 5: What next ..
Journey So far .You will learn how Large Language Models (LLMs) work and how to run models like Llama 3 locally using Ollama without depending entirely on ρáíd cloud APIs. Using Spring AI, you will create intelligent REST APIs capable of understanding prompts, generating AI responses, maintaining conversational memory, and handling real-world AI interactions.
This project also introduces important AI engineering concepts such as Prompt Engineering, Tool Calling, AI Agents, and Model Context Protocol (MCP). You will understand how enterprise AI systems connect with external APIs, databases, and tools to perform smart actions beyond simple text generation.
Using Postman, you will test and explore AI endpoints like a real enterprise application. H2 Database will help you store chat history, user interactions, and AI conversation data for better context management.
We will start with introduction to Prompt engineering to Tooling, LLM installation to respond the simple chat with some data.
By the end of this project, you will not only build a complete AI application but also understand modern enterprise AI architecture, AI orchestration flow, local model deployment, and how Spring Boot developers can build scalable AI-powered systems from scratch.
Happy Learning
Who this course is for
Java and Spring Boot developers
Backend developers interested in building AI-powered REST APIs, chat applications, and enterprise AI systems.
Software engineers who want hands-on experience with Spring AI, Ollama, LLM integration, Tool Calling, and AI Agents.
Students and professionals who want to understand how modern Generative AI applications are designed, integrated, and deployed in real-world enterprise environments.Homepage
Code:
https://www.udemy.com/course/build-ai-application-with-spring-boot-ollama-and-mcp
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