Spring Ai: Beginner To Guru

Spring Ai: Beginner To Guru
Published 5/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English

| Size: 2.77 GB[/center]
| Duration: 4h 28m
Use Java to Unlock the Power of OpenAI's ChatGPT Artificial Intelligence (AI) with Spring AI

What you'll learn

Learn how to use Spring AI to interact with OpenAI

How to write effective Prompts for Large Language Models

Use Retrieval Augmented Generation to Improve Response Capabilities

Generate Speech from Text

Generate Text from Speech

Requirements

Java and Spring Experience is Required

Understanding of working with RESTful APIs

Able to use Docker to run a Docker Compose Script

Description

Traditionally accessing Artificial Intelligence Models, such as OpenAI's ChatGPT, has been the domain of programming languages Python and jаvascript. Not any more. Spring AI unlocks the power of Generative AI for Java developers. The Spring AI project aims to streamline the development of applications that incorporate artificial intelligence functionality without unnecessary complexity. Spring AI provides support for all major Artificial Intelligence models, including:OpenAIAzure OpenAIAmazon BedrockHuggingFaceOllama Google VertextAI (PaLM2 and Gemini)Mistral AIAntrhopicWatsonxAISpring AI also supports image generation AI models from OpenAI and Stability. Retrieval Augmented Generation is an important use case for dealing with AI models. Spring AI includes robust support for all major Embedding Models and all popular vector databases. No prior experience with AI is needed for this course. You will start the course with a solid overview of what Artificial Intelligence is. Next you'll have a hands on section to develop a RESTful API to ask OpenAI's ChatGPT questions. In this section, you will learn how we can instruct the model to return data in the format we desire. Since no AI experience is required, the next section of the course builds upon what you learned with a formal look at Prompt Engineering. Prompt Engineering is a collection techniques to improve the quality and accuracy of responses from AI Models.Retrieval Augmented Generation (RAG) is an important technique to provide Large Language Models with additional information required to the user's query to complete specialized tasks. You will see how we can use RAG to develop AI experts to perform high specialized tasks. The AI models are not just limited to working with textual information. In this course you will also see how to use AI to create images, create audio files from text, and how to transcribe audio files to text. Learn all this and more in Spring A:I Beginner to Guru. Enroll today!

Overview

Section 1: Introduction

Lecture 1 Course Introduction

Lecture 2 Instructor Introduction

Lecture 3 Getting the Most Out of Your Course

Lecture 4 Setting Up Your Development Environment

Lecture 5 Is Your IDE Free Like A Puppy?

Lecture 6 Free 120 Day IntelliJ Trial

Lecture 7 Course Slack Room - Chat with Your Instructor and Other Students

Lecture 8 Github Workflow

Section 2: Introduction to AI

Lecture 9 Introduction

Lecture 10 Types of Artificial Intelligence

Lecture 11 Introduction to Large Language Models (LLMs)

Lecture 12 Overview of OpenAI

Section 3: Introduction to Spring AI with OpenAI

Lecture 13 Introduction

Lecture 14 Get Your OpenAI API Key

Lecture 15 Create New Spring Boot Project

Lecture 16 Configure OpenAI API Keys

Lecture 17 Add OpenAI Service

Lecture 18 Exploring LLM Capabilities

Lecture 19 Create Spring MVC Controller

Lecture 20 Test Controller with Postman

Lecture 21 Using Prompt Templates

Lecture 22 Directing OpenAI to format the Response

Lecture 23 Directing OpenAI to Respond with JSON

Lecture 24 Binding OpenAI Responses With JSON Schema

Lecture 25 OpenAI Response Meta Data

Section 4: Prompt Engineering

Lecture 26 Introduction

Lecture 27 Overview on Prompt Engineering

Lecture 28 Giving Clear and Precise Instructions

Lecture 29 Giving the Model Time to Think

Lecture 30 Summarizing

Lecture 31 Inferring

Lecture 32 Zero Shot and Few Shot Prompting

Lecture 33 Chain of Thought

Lecture 34 Using System Messages

Section 5: Retrieval Augmented Generation - RAG

Lecture 35 Introduction

Lecture 36 Overview of Retrevial Augmented Generation

Lecture 37 Configure Vector Store

Lecture 38 Configure Vector Store Data Load

Lecture 39 Returning Documents from Vector Store

Lecture 40 Improving Prompt Performance - Embedding Config

Lecture 41 Improving Prompt Performance - Trimming Data

Lecture 42 Providing Document Meta Data

Section 6: AI Recommendation Expert with RAG

Lecture 43 Introduction

Lecture 44 Overview of Towing

Lecture 45 Spring Boot Project Review

Lecture 46 Configure Milvus Vector Database

Lecture 47 Vector Store Data to Load

Section 7: OpenAI Functions

Lecture 48 Introduction

Lecture 49 Overview of Function Calling with OpenAI

Lecture 50 Spring Boot Project Review

Lecture 51 Get API Ninjas API Key

Lecture 52 Use System Message to Improve Model Response

Section 8: Spring AI Image Generation and Vision

Lecture 53 Introduction

Lecture 54 Overview of Image Generation with OpenAI

Lecture 55 Code Review of Spring Boot Project

Lecture 56 Using DALL-E 3 OpenAI Model

Lecture 57 Implement Spring MVC Endpoint

Section 9: Spring AI Text to Speech

Lecture 58 Overview of Text to Speech with OpenAI

Lecture 59 Spring Boot Project Review

Lecture 60 Implement Spring MVC Endpoint

Section 10: Spring AI Speech to Text

Lecture 61 Overview of Speech to Text

Any Java Developer wishing to get started using OpenAI