Build AI Application with Spring boot, Ollama and MCPPublished 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
⚡ 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 idea
DescriptionHave you ever wondered how ChatGPT-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
✨ resources
Section 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 communication
Section 3: Prompt Engineering fundamental✨ Prompt Engineering Fundamentals
✨ Context Engineering in AI System
Section 4: Project Development✨ Introduction to Spring AI
✨ Project Structure
✨ Create Employee Service
✨ Create MCP Server
✨ Create Chat Client
✨ Bug Fix
Section 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 paid 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 LearningWho 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.
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