Spring Ai - Genai
Published 6/2025
Created by Navin Reddy
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 44 Lectures ( 3h 32m ) | Size: 3.33 GB
Build AI-powered Spring Boot app. using SpringAI with OpenAI, Ollama, RAG, vector databases, with multimodal capability.
What you'll learn
Easily Integrate Model-as-a-Service(OpenAI) and Open-Source(Ollama) AI Models
Develop Context-Aware Conversational AI
Create Multimodal(Text, Audio, Image) and Structured AI Applications
Integrate Retrieval-Augmented Generation (RAG) to enhance prompt effectiveness
Dive into vector databases and discover how they power modern AI applications
Requirements
To enroll, you'll need basic Spring Boot knowledge and Java programming experience.
Description
Spring AI-Gen AI (TELUSKO)This comprehensive course on Spring AI is your gateway to building intelligent, AI-powered Java applications. It leverages Spring AI, the official module within the Spring framework, designed to seamlessly integrate Large Language Models (LLMs) and a broad spectrum of AI capabilities into your Spring Boot projects.You'll develop essential skills for integrating diverse AI models, from popular model-as-a-service provider like OpenAI (GPT-4o) to open-source LLM providers like Ollama (Mistral and Deepseek). This is achieved through Spring AI's standardized API, offering remarkable portability and minimizing vendor lock-in.A significant portion of the curriculum focuses on developing sophisticated conversational AI systems using the intuitive ChatClient API and ChatModel, enabling dynamic and natural interactions. Furthermore, you'll master Retrieval-Augmented Generation (RAG), a critical technique that empowers LLMs with external, up-to-date, and domain-specific knowledge. This involves deep dives into vector embeddings and practical experience with various vector databases like PgVector, Redis, and Spring AI's SimpleVectorStore, ensuring your AI responses are contextually relevant and accurate.Beyond conventional text-based AI, the course ventures into multimodal applications, covering capabilities like image and audio processing, including text-to-speech and speech-to-text. This expands the possibilities for creating truly immersive and interactive applications. You'll also learn the art of prompt engineering through templates and advisors for enhanced AI interactions, and crucially, how to transform raw AI outputs into neatly structured Java objects (List, Bean, Map) for seamless integration into your application's logic.This course is ideally suited for Java developers eager to add cutting-edge AI functionalities to their Spring Boot applications, backend developers exploring modern AI integration patterns, and teams dedicated to building the next generation of intelligent, data-driven applications. A solid foundation in Spring Boot and Java programming is recommended to maximize your learning experience. By completing this course, you will be well-equipped to transform your Spring applications with advanced AI features, ensuring you remain at the forefront of the rapidly evolving AI-driven development landscape.
Who this course is for
This course is for Java, Spring, and backend developers aiming to integrate AI capabilities into Spring Boot applications, as well as for teams building intelligent, next-generation applications
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