This Generative AI for Dynamic Java Web Applications comprehensive course is designed to equip developers with the knowledge and hands-on skills to integrate Generative AI capabilities into dynamic Java web applications. Participants will learn how to leverage advanced AI models to automate content generation, enhance user experiences, and build intelligent, interactive web applications. The program covers end-to-end development, including AI-driven APIs, natural language processing, real-time data handling, and seamless integration with Java frameworks like Spring Boot and Jakarta EE. By the end of the course, learners will be able to design, develop, and deploy AI-powered web applications that are scalable, responsive, and innovative, opening doors to exciting career opportunities in modern software development.
Module 1: Introduction to Generative AI & Java Web Development Fundamentals of Generative AI and its applications Overview of Java web development Setting up IDEs (IntelliJ IDEA, Eclipse), JDK, Maven/Gradle Understanding client-server architecture and web protocols.
Module 2: Core Java & Object-Oriented Programming for Web Applications Advanced Java concepts: Collections, Streams, and Generics Object-Oriented Programming principles for scalable design Exception handling and debugging in web contexts.
Module 3: Web Technologies & Front-End Integration HTML5, CSS3, JavaScript, AJAX, and responsive design DOM manipulation and event handling Integrating front-end with Java back-end.
Module 4: Advanced Java Web Frameworks Spring Boot and Jakarta EE deep dive MVC architecture, dependency injection, and RESTful API creation Security features: Authentication, authorization, and JWT.
Module 5: Database Management & Data Handling Relational databases: MySQL, PostgreSQL NoSQL databases: MongoDB CRUD operations, ORM with Hibernate Data modeling and schema design for AI applications.
Module 6: Introduction to Machine Learning & NLP ML fundamentals: supervised, unsupervised, reinforcement learning Natural Language Processing conceptsUsing NLP libraries: NLTK, SpaCy, OpenNLP Preprocessing and cleaning data for AI models.
Module 7: Generative AI Integration Overview of generative models (GPT, Transformer-based) Integrating AI APIs (OpenAI, Hugging Face) with Java Building AI-driven chatbots, content generators, and recommendation systems AI-based personalization in web applications.
Module 8: Real-Time Data Processing & AI Workflows Handling streaming and large-scale data in web apps Data preprocessing pipelines and feature engineering AI model deployment for real-time inferencen Performance monitoring and optimization.
Module 9: Testing, Optimization & Deployment Unit testing, integration testing, and JUnit/Selenium Application performance tuning and AI workflow optimization Containerization using Docker Cloud deployment: AWS, Azure, GCP.
Module 10: Capstone Project & Industry Applications End-to-end development of an AI-powered dynamic Java web application Implementing frontend, backend, and AI integration Real-world use cases: e-commerce, chatbots, content automation Project presentation, documentation, and evaluation.
Mobile: 9100348679
Email: coursedivine@gmail.com
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