Spring Ai: From Ai Fundamentals To Spring Ai Insights

Use Java to Harness the Power of Spring AI with OpenAI

What you'll learn

Explore Spring AI implementation in depth. Understand the internal workings of Models, ChatClient, Advisors, Prompts, Messages, Function Calling, and much more.

Build a strong foundation in AI fundamentals by learning key concepts such as tokens, embeddings, RAG, vector databases, and cosine similarity.

Develop practical skills in designing, coding, and integrating essential features like Image and Voice generation, Image Recognition.

Learn how to use Spring AI to integrate any OpenAI model to your application

Requirements

Basic Java Knowledge: Familiarity with the Java programming language and object-oriented programming principles.

Experience with Spring Framework: General familiarity with Spring Boot and core Spring concepts is sufficient.

Development Environment Setup Skills: Ability to set up a Java development environment and use coding tools.

Description

Unlock the full potential of generative AI in your Java applications with Spring AI. This comprehensive course, "Spring AI: From AI Fundamentals to Spring AI Insights" is designed to guide Java and Spring developers through the process of integrating powerful AI technologies directly into their projects using the Spring Framework.We start with a solid introduction to the fundamentals of artificial intelligence, covering key concepts that lay the foundation for understanding how AI and large language models (LLMs) work. This initial segment ensures that even those new to AI can grasp the essential principles before diving deeper.From there, we guide you through the process of setting up your development environment by cloning a GitHub project, and you’ll learn how to register and manage your OpenAI API key to enable seamless integration. As you progress, you’ll explore the powerful capabilities of Spring AI, understanding how to build projects that utilize OpenAI models effectively. We will delve into practical applications, showing you how to work with Prompts and Messages, create and customize Prompt Templates, and use essential components like BeanOutputConverter. Additionally, you’ll learn to configure ChatClient and ChatOptions, as well as implement Function Calling to expand the functionalities of your applications.You will discover techniques for crafting effective Prompts that guide AI models, including methods like Zero-shot and Few-shot prompting, and Chain-of-Thought reasoning, which significantly improves the accuracy and relevance of responses. This will help you to not only instruct the AI models but also optimize their behavior for different contexts.We also focus on building practical, real-world projects, including a robust chat application. You’ll gain hands-on experience in creating chat APIs, utilizing ChatMemory and ChatMemoryAdvisors, and setting Chat Memory Parameters to enhance user interaction. These projects will provide you with the practical skills to build responsive chat systems that can be integrated into various applications.We will introduce you to more advanced AI capabilities, including Image Generation and Speech Synthesis. You’ll also learn about cutting-edge techniques such as Retrieval-Augmented Generation (RAG), the use of Embeddings, Vector Databases, and the application of Cosine Similarity, all of which will enhance your ability to create sophisticated, intelligent applications.Towards the end of the course, you will have the opportunity to develop a comprehensive AI-powered Calorie Counter Application using Image Recognition, RAG and Vector DB. No prior experience in AI is required; all you need is a familiarity with Java and Spring, and this course will guide you through everything else you need to succeed.

Overview

Section 1: Introduction

Lecture 1 Course Introduction

Lecture 2 Github clone project.

Section 2: AI Introduction

Lecture 3 Artificial Intelligence basics

Lecture 4 Large Language Models (LLMs)

Section 3: Spring AI capabilities. OpenAI

Lecture 5 Register OpenAI key

Lecture 6 Create project

Lecture 7 OpenAI Integration

Lecture 8 Prompts and Messages

Lecture 9 Prompt Template

Lecture 10 BeanOutputConverter

Lecture 11 ChatClient. ChatOptions

Lecture 12 Function calling

Section 4: Prompt Engineering

Lecture 13 Introduction

Lecture 14 Create project

Lecture 15 Write clear instructions

Lecture 16 Zero shot, Few shot Prompting

Lecture 17 Chain-of-Thought

Section 5: Chat with model

Lecture 18 Introduction

Lecture 19 Create project

Lecture 20 Simple API

Lecture 21 ChatMemory & ChatMemoryAdvisors

Lecture 22 Chat memory parameters

Section 6: Calorie counter. Voice/image generation and recognition.

Lecture 23 Introduction

Lecture 24 Create project

Lecture 25 Image generation

Lecture 26 Speech generation

Lecture 27 RAG. Vector DB

Lecture 28 Embeddings. Vectors. Cosine similarity.

Lecture 29 Calorie counter

This course is designed for developers and software engineers who want to expand their skills by integrating AI capabilities into their applications using the Spring Framework