Java Meets AI - A Hands On Guide to Building LLM Powered Applications with LangChain4j

Übersicht

Lehrplan

• Introduction to AI and Large Language Models
Overview of AI and its applications
Understanding Large Language Models and their capabilities
• Setting Up the Development Environment
Installing Java and necessary tools
Introduction to LangChain4j
Setting up a Java project for AI integration
• Basics of LangChain4j
Understanding the LangChain4j architecture
Key components and interfaces
Writing a simple LangChain4j application
• Integrating Large Language Models in Java
Choosing and accessing language models
Using LangChain4j to connect with language models
Sending queries and processing responses
• Building AI-Powered Java Applications
Designing application workflows with LangChain4j
Handling model inputs and outputs effectively
Error handling and debugging best practices
• Case Study: Developing a Chatbot
Designing a conversational flow
Implementing chat functionality using LangChain4j
Enhancing responses with contextual awareness
• Advanced LangChain4j Features
Utilizing advanced APIs and customization
Integrating additional AI services and tools
Performance tuning and optimization techniques
• Security and Ethical Considerations
Understanding data privacy and security in AI applications
Addressing biases and ethical concerns
Implementing responsible AI practices
• Testing and Deployment
Writing test cases for AI-driven features
Continuous integration and deployment strategies
Monitoring and maintenance of AI applications
• Future Trends and Developments in AI and LangChain4j
Emerging technologies and innovations in AI
Expanding capabilities of Large Language Models
Future directions for LangChain4j
• Course Conclusion and Next Steps
Recap of key learning points
Resources for further learning and development
Opportunities for real-world application and projects

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Fachgebiete

Conference Talks