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Starts 8 June 2025 16:02
Ends 8 June 2025
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Overview
Hands-on guide to integrating AI and Large Language Models into Java applications using LangChain4j, enabling developers to create powerful AI-driven solutions.
Syllabus
- Introduction to AI and Large Language Models
- Setting Up the Development Environment
- Basics of LangChain4j
- Integrating Large Language Models in Java
- Building AI-Powered Java Applications
- Case Study: Developing a Chatbot
- Advanced LangChain4j Features
- Security and Ethical Considerations
- Testing and Deployment
- Future Trends and Developments in AI and LangChain4j
- Course Conclusion and Next Steps
Overview of AI and its applications
Understanding Large Language Models and their capabilities
Installing Java and necessary tools
Introduction to LangChain4j
Setting up a Java project for AI integration
Understanding the LangChain4j architecture
Key components and interfaces
Writing a simple LangChain4j application
Choosing and accessing language models
Using LangChain4j to connect with language models
Sending queries and processing responses
Designing application workflows with LangChain4j
Handling model inputs and outputs effectively
Error handling and debugging best practices
Designing a conversational flow
Implementing chat functionality using LangChain4j
Enhancing responses with contextual awareness
Utilizing advanced APIs and customization
Integrating additional AI services and tools
Performance tuning and optimization techniques
Understanding data privacy and security in AI applications
Addressing biases and ethical concerns
Implementing responsible AI practices
Writing test cases for AI-driven features
Continuous integration and deployment strategies
Monitoring and maintenance of AI applications
Emerging technologies and innovations in AI
Expanding capabilities of Large Language Models
Future directions for LangChain4j
Recap of key learning points
Resources for further learning and development
Opportunities for real-world application and projects
Subjects
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