Spring AI for beginners : Build GenAI LLM Apps in Easy Steps

Welcome to Spring AI for Beginners!

This course is designed to provide a gentle, step-by-step introduction to Spring AI, guiding you

from the basics to more advanced concepts. Whether you're a complete novice or have some

experience with AI, this course will help you understand and leverage the power of Spring AI for

building AI-powered applications.

Course Goals:

- Gradual Learning: Learn Spring AI gradually from basic to advanced topics with clear and

concise instructions.

- Comprehensive Understanding: Understand why Spring AI is a powerful tool for building AI

applications and how it simplifies the integration of language models into your projects.

- Hands-On Experience: Gain practical experience with essential Spring AI features such as

prompt templates, chains, agents, document loaders, output parsers, and model classes.

What You Will Learn:

- Introduction to Spring AI: Get started with the basics of Spring AI and understand its core

concepts.

- Building Blocks of Spring AI: Learn about prompt templates, chains, agents, document loaders,

output parsers, and model classes.

- Creating AI Applications: See how these features come together to create a smart and flexible

- Practical Coding: Write and run code examples to get a hands-on sense of how Spring AI

development looks like.

Course Structure:

- Concise Chapters: Each chapter focuses on a specific topic in Spring AI programming,

ensuring you gain a deep understanding of each concept.

- Interactive Learning: Code along with the examples provided to reinforce your learning and build

your skills.

By the end of this course, you will:

Learn what Spring AI is how it simplifies  using LLMs in our applications

Use OpenAI LLMs in a Spring Boot application

Use Open Source LLMs like Mistral,Gemma in a Spring Boot application

Run Open Source LLMs on your local machine using OLLAMA

Use PromptTemplates to reuse and build dynamic prompts

Learn why and how to maintain Chat History

Learn what embeddings are and use the Embeddings Model to find text Similarity

Understand what a Vector Store is and use it to store and retrieve Embeddings

Understand the process of Retrieval Augmented Generation(RAG)

Implement  (RAG) to use our own data with LLMs in simple steps

Analyze images using Multi Modal Models

Build multiple LLM APPs using Thymeleaf and Spring AI

All in simple steps