In-Depth: Developing Generative AI Applications with Spring
Published 9/2024
Duration: 8h39m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.72 GB
Genre: eLearning | Language: English

Mastering Spring AI and Advanced Generative AI Technologies

What you'll learn
Understand AI Fundamentals: Gain a solid foundation in essential AI concepts, including tokens, embeddings, semantic search, and vector stores.
Explore Prompt Engineering and RAG: Learn about prompt engineering techniques and Retrieval-Augmented Generation (RAG) for improving AI interactions.
Utilize the Spring AI project to effectively develop generative AI applications based on Spring Boot.
Engage in Extensive Hands-On Labs: Participate in practical labs that provide direct experience with the Spring AI framework and foundational models.
Handle Practical Programming Challenges: Learn best practices for storing access credentials, managing errors and retries, and setting custom parameters, etc.
Utilize Key Parameters Effectively: Understand and apply common parameters like temperature, topP, max tokens, logit bias, and stop sequences.
Emphasize Automated Testing: Incorporate automated testing practices to ensure the reliability and performance of generative AI applications.
Gain practical experience working with OpenAI, Azure AI, Amazon Bedrock, Ollama, Anthropic, Cohere, Ollama, StabilityAI, and others.

Requirements
Students should have basic proficiency in Java, including experience with the Spring Framework and Spring Boot. To complete the hands-on labs (recommended), students must also have access to a computer capable of running Java and an integrated development environment (IDE) of their choice, such as IntelliJ IDEA, Eclipse, or Visual Studio Code.
Some hands-on labs require setting up accounts and credentials with AI model providers. These services may have associated charges, which are not covered by the course fee, though the overall cost is minimal.

Description
Unlock the potential of generative AI with our immersive course, "In-Depth: Developing Generative AI Applications with Spring." This course is crafted for Java and Spring developers eager to integrate cutting-edge AI technologies into their applications. Start your journey by exploring the new Spring AI project, a powerful framework that facilitates the development of advanced AI solutions within Spring-based environments.
You will gain deep insights into essential AI concepts such as tokens and prompt engineering, laying a solid foundation for more advanced topics. As you progress, delve into advanced technologies such as embeddings, VectorStores, and semantic search, understanding how they empower Retrieval-Augmented Generation (RAG) to enhance AI interactions.
Our extensive hands-on labs will provide practical experience with the Spring AI framework and real-world foundational models from leading providers like OpenAI, Azure, AWS Bedrock, Ollama, Anthropic, Cohere, StabilityAI, and others. You'll develop Spring Boot applications that interact seamlessly with these models, ranging from chatbots to image generators.
We'll also address practical programming challenges, including managing access credentials, handling errors and retries, and configuring default and custom parameters. Emphasis on automated testing will ensure your applications are both reliable and high-performing.
With engaging labs, real-world insights, and a focus on the latest advancements in AI and Spring, this course will empower you to innovate and excel in the dynamic field of generative AI. Seize this opportunity to advance your skills and transform your development process with cutting-edge AI technology!
Who this course is for:
This course is intended for software developers having basic, intermediate, or advanced knowledge of Java, Spring, and Spring Boot

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