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Starts 8 June 2025 16:02

Ends 8 June 2025

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

Hands-on guide to integrating AI and Large Language Models into Java applications using LangChain4j, enabling developers to create powerful AI-driven solutions.
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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
  • 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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