Best Full Stack Java + AI Developer Course Training Institute

Full Stack Java + AI

Full Stack Java + AI is a comprehensive software development program that combines modern Java Full Stack technologies with Artificial Intelligence. This course enables students to build scalable web applications, develop RESTful APIs, integrate AI-powered features, and deploy intelligent enterprise applications using Java, Spring Boot, React, Machine Learning, and Generative AI technologies.

Join the Course View Syllabus

Commercial

Industry Standard

Every 2 Weeks

New Batch Starts

Classroom / Remote

Training Modes

@SpringBoot

Application

mvn

clean install

BUILD

SUCCESS

List<User>

users =

Full Stack Java + AI

REST APIs

SQL & Databases

Docker

AWS Cloud

Git & GitHub

Production Deployment

Full Stack Java + AI

REST APIs

SQL & Databases

Docker

AWS Cloud

Git & GitHub

Production Deployment

Program Overview

Full Stack Java + AI Includes

Front-End Development

Learn to create responsive and interactive web applications using HTML5, CSS3, Bootstrap, JavaScript, React.js, and modern UI development practices.

Core Java & Advanced Java

Master Java programming concepts including OOP , Collections, Exception Handling, Multithreading, JDBC, File Handling, and Java 8 features.

Spring Framework & Spring Boot

Develop enterprise-level applications using Spring Core, Spring MVC, Spring Boot, Spring Security, REST APIs, Hibernate, and Microservices.

Database Management

Learn SQL, MySQL, MongoDB, database design, optimization, and integration with Java applications.

Artificial Intelligence

Understand AI concepts, intelligent systems, Natural Language Processing (NLP), Computer Vision basics, and AI-powered application development.

Machine Learning

Build predictive models using Python libraries and understand how Machine Learning integrates with Java-based applications through APIs and services.

Generative AI

Learn Prompt Engineering, Large Language Models (LLMs), OpenAI API, Google Gemini API, LangChain, Hugging Face, Vector Databases, and Retrieval-Augmented Generation (RAG).

AI Automation

Build AI-powered chatbots, automate workflows, integrate AI APIs, and create intelligent enterprise solutions using Java and AI technologies.

Prerequisites & Eligibility

Skills & Qualifications

The Full Stack Java + AI course is suitable for beginners, students, graduates, software professionals, and career switchers interested in modern software development and Artificial Intelligence. Recommended skills include: • Basic Computer Knowledge

Note: Designed for students, freshers, and IT working professionals aiming to master Full Stack Java + AI with commercial project experience and 100% placement support.

Key Competencies Covered

OpenAI API Google Gemini API LangChain Hugging Face Vector Databases ChromaDB Pinecone (Introduction) AI Agents Prompt Engineering RAG Docker Git & GitHub

Curriculum Breakdown

Full Stack Java + AI Syllabus

Comprehensive hands-on modules extracted directly from our official training document.

Module 1 – Core Java

Module 1 Topic Coverage (Theory + Live Coding)

Java Fundamentals

Variables & Data Types

Operators

Control Statements

Arrays

Methods

Object-Oriented Programming

Exception Handling

Collections Framework

Multithreading

File Handling

Java 8 Features

Includes Hands-On Labs Real-World Practice

Module 2 – Advanced Java

Module 2 Topic Coverage (Theory + Live Coding)

JDBC

Servlets

JSP

Maven

Build Tools

Includes Hands-On Labs Real-World Practice

Module 3 – Front: End Development

Module 3 Topic Coverage (Theory + Live Coding)

HTML5

CSS3

Bootstrap

JavaScript

React.js

Includes Hands-On Labs Real-World Practice

Module 4 – Spring Technologies

Module 4 Topic Coverage (Theory + Live Coding)

Spring Core

Spring MVC

Spring Boot

Spring Security

Hibernate

REST API Development

Microservices

Includes Hands-On Labs Real-World Practice

Module 5 – Database

Module 5 Topic Coverage (Theory + Live Coding)

SQL

MySQL

MongoDB

Database Design

Includes Hands-On Labs Real-World Practice

Module 6 – Version Control

Module 6 Topic Coverage (Theory + Live Coding)

Git

GitHub

Includes Hands-On Labs Real-World Practice

Module 7 – Artificial Intelligence

Module 7 Topic Coverage (Theory + Live Coding)

AI Fundamentals

AI Applications

NLP Basics

Computer Vision Basics

AI Ethics

Includes Hands-On Labs Real-World Practice

Module 8 – Machine Learning

Module 8 Topic Coverage (Theory + Live Coding)

Data Preprocessing

Regression

Classification

Clustering

Model Evaluation

Includes Hands-On Labs Real-World Practice

Module 9 – Generative AI

Module 9 Topic Coverage (Theory + Live Coding)

Prompt Engineering

OpenAI API

Google Gemini API

Hugging Face

LangChain

Vector Databases

RAG

AI Chatbots

Includes Hands-On Labs Real-World Practice

Module 10 – AI Automation

Module 10 Topic Coverage (Theory + Live Coding)

AI Agents

Workflow Automation

AI API Integration

Intelligent Enterprise Applications

Includes Hands-On Labs Real-World Practice

Module 11 – Deployment

Module 11 Topic Coverage (Theory + Live Coding)

Docker

Cloud Deployment

CI/CD

Application Deployment

Includes Hands-On Labs Real-World Practice

Practical Labs

Projects You'll Build

Build commercial portfolio-grade applications during your training.

Enterprise Banking & Payment Application

Build a secure core banking platform using Java 21, Spring Boot microservices, and Spring Security.

AI-Integrated E-Commerce Platform

Develop a scalable online marketplace with React frontend, Spring Boot backend, and AI search integration.

Healthcare & Doctor Consultation System

Create a hospital appointment and telemedicine management system with MySQL and REST APIs.

Flight & Hotel Reservation Engine

Build an online booking engine with distributed microservices, Redis caching, and payment gateway integration.

Employee Attendance & Payroll Portal

Develop an automated human resource and payroll calculation management system.

Real-Time Collaborative Document Editor

Build a collaborative workspace with WebSocket synchronization and Docker containerization.

Got Questions?

We are here to help.

Everything you need to know before enrolling in the Full Stack Java + AI program.

01 What is Full Stack Java + AI?

It is a complete program that combines Java Full Stack development with Artificial Intelligence, enabling students to build intelligent enterprise web applications.

02 Who can join this course?

Students, graduates, working professionals, software developers, and career changers can join. No prior AI knowledge is required.

03 Do I need Java knowledge before joining?

No. The course starts with Core Java fundamentals and gradually progresses to advanced Full Stack and AI concepts.

04 Will I build real-world AI projects?

Yes. Students work on enterprise-level AI projects, including chatbots, resume screening systems, AI-powered web applications, and intelligent automation tools.

05 Does the course include Spring Boot?

Yes. Spring Boot, Spring MVC, Spring Security, Hibernate, REST APIs, and Microservices are key components of the curriculum.

06 Will I learn Generative AI?

Yes. You'll learn Prompt Engineering, OpenAI API, Google Gemini API, LangChain, Hugging Face, Vector Databases, and Retrieval-Augmented Generation (RAG).

07 What AI tools and technologies are covered?

• OpenAI API • Google Gemini API • LangChain • Hugging Face • Vector Databases • ChromaDB • Pinecone (Introduction) • AI Agents • Prompt Engineering • RAG • Docker • Git & GitHub

08 Is placement assistance provided?

Yes. Students receive resume preparation, mock interviews, real-time project experience, internship opportunities, career guidance, and placement assistance.

09 Will I receive a certificate?

Yes. Upon successful completion of the course and projects, students receive a Course Completion Certificate. Internship certificates may also be awarded based on eligibility.

10 What career opportunities are available after completing this course?

Graduates can pursue roles such as: • Full Stack Java Developer • Java Backend Developer • Spring Boot Developer • AI Application Developer • AI Software Engineer • Java Full Stack Engineer • Microservices Developer • Machine Learning Engineer • Generative AI Developer • AI Integration Engineer • Software Engineer • Technical Consultant • Enterprise Application Developer • AI Solutions Developer

Still have questions about this course?

Speak directly with our senior course advisors to customize your learning path.

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