GenAI for Busy Java Developers

This video course empowers Java engineers with the basic knowledge and skills needed to harness the capabilities of generative AI tools for various aspects of the production software process.
Developed for beginner and early intermediate Java developers, it explores the impact of Machine Learning on the Java ecosystem and features hands-on coding using tools such as OpenAI ChatGPT, Google Gemini, Anthropic Claude, and other GenAI services using the LangChain4j API. With a focus on practical applications, participants will gain proficiency in GenAI, an understanding of context, learn about embeddings, and how to responsibly integrate GenAI into Java applications.
Attendees will
Learn the skills they need in order to apply generative AI to real-world software development. Enterprise developers will learn the fundamentals of generative AI and how to best apply them to reliably put GenAI applications into production.
Understand programmatic interfaces to GenAI using REST APIs and featuring the LangChain4J Java API, including many source code examples covering different prompt techniques, streaming, embeddings, templates, context, Retrieval-Augmented Generation (RAG) and an introduction to agents
Architect and implement a basic chatbot application that understands private document sets.
Skill Level
Beginner to Early Intermediate
Learn How To
Differentiate between the two basic types of deep learning
Structure prompts and select techniques that produce useful output
Use LangChain4j to create a working GenAI application
Apply embeddings to various use cases
Manage context for effective LLM responses
Choose an appropriate vector database and what to store in that database
Create tools and understand the basics of agents
Course Requirement
Basic Java knowledge
Who Should Take This Course
Java developers who manage production deployment and need to understand how to apply generative AI in their daily workflow
Programmers with modern software development responsibilities who need to use AI tools for code creation or to create applications that leverage GenAI services