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AI Agent Architecture in Java with Generative AI · LearnSpace
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AI Agent Architecture in Java with Generative AI

Курс от Vanderbilt University
Средний≈ 7.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Master the Art of Building Intelligent Java Agents That Think, Reason, and Act Unlock the full potential of Java for creating autonomous AI agents that solve complex problems without constant human direction. In this comprehensive course on AI Agents and Agentic AI with Java & Generative AI, you'll learn how to architect sophisticated agent systems that leverage Java's robust ecosystem and enterprise-grade capabilities. This course takes you beyond the foundations covered in the AI Agents and Agentic AI with Java & Generative AI course to explore advanced patterns for building truly intelligent agents in Java. You'll delve into specialized techniques like self-prompting, expert personas, document-as-implementation, and multi-agent orchestration - all implemented with Java's powerful frameworks and libraries. ## What You'll Learn: - **Self-Prompting Patterns in Java**: Build agents that dynamically adopt different thinking modes to handle specialized tasks, transforming unstructured data into structured formats with clean Java implementations - Java-Based Expert Persona Systems: Implement consultation frameworks where agents can invoke domain experts for specialized knowledge while maintaining clean architecture - Document-as-Implementation: Use Java's powerful file handling to create systems where human-readable documents become executable business logic - Multi-Agent Collaboration with Java: Design sophisticated memory sharing and coordination mechanisms between specialized Java agents - Progress Tracking & Planning: Implement robust planning and reflection capabilities using Java's enterprise-grade tooling - Java Agent Safety & Trust Systems: Build transaction management and safety mechanisms that leverage Java's exception handling and security features By the end of this course, you'll be equipped to build complex, enterprise-ready agent systems in Java that can reason across multiple domains, handle complex workflows, and safely interact with real-world systems. Whether you're building productivity tools, automating complex business processes, or creating intelligent assistants, you'll have the Java-specific knowledge to implement agentic AI solutions that provide genuine business value. This course will teach you these concepts using OpenAI's APIs, which require paid access, but the principles and techniques can be adapted to other LLMs.

Навыки, которые вы освоите

Agentic systemsPrompt EngineeringJava ProgrammingPrompt PatternsGenerative AI AgentsPlan ExecutionSoftware Design DocumentsAgentic WorkflowsGenerative AIAI WorkflowsPersona (User Experience)LLM ApplicationAI IntegrationsDocument ManagementSecure CodingSoftware Design PatternsAI OrchestrationJavaBusiness LogicOpenAI API

Программа курса

5 модулей · 37 учебных материалов

01Extending AI Agents with Self-Prompting16 материалов
Prompts as ComputationВидеоSelf-Prompting & Clean Separation of AI Agent ReasoningPLUGINGetting & Running the Code ExamplesЧтениеBridging Computer Tools & Unstructured Data with Prompting - the AI ShimВидео

Учитесь у экспертов

Dr. Jules White

Professor of Computer Science

AI Agent Architecture in Java with Generative AI
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 7.6 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский, Казахский, Венгерский

Часть программы вашего университета
AI Agent Structured Data ExtractionPLUGIN
An Invoice Processing AgentPLUGIN
Learning More & Staying ConnectedЧтение
The Persona Pattern and Reasoning - Personas are an efficient programming abstractionВидео
The Persona PatternВидео
Consulting Experts or Simulating with the Persona PatternPLUGIN
Format of the Persona PatternЧтение
Simple Multi-Agent Systems with PersonasВидео
The Persona Abstraction & AgentsPLUGIN
Invoice Processing with ExpertsPLUGIN
Using Human Policies for Document-as-ImplementationPLUGIN
Persona & Self-Prompting ReviewЗадание
02AI Agent Design Principles & Safety3 материалов
The MATE Design Principles for AI AgentsВидеоMATE Design Principles in CodePLUGINAI Agents & Environment SafetyPLUGIN
03Multi-Agent Systems8 материалов
Introduction to Multi-Agent SystemsВидеоBuilding Multi-Agent Systems: Agent-to-Agent CommunicationPLUGINAgent Interaction & MemoryВидеоAgent Interaction Patterns with MemoryPLUGINRemoving Noise: Focusing Agent AttentionВидеоAdvanced Agent InteractionPLUGINProviding Agentic AI Information About the WorldВидеоAgent Interaction ArchitecturesЗадание
04Dependency Injection for Tools3 материалов
Isolating Agents from Accidental ComplexityВидеоClean AI Tools with Dependency InjectionPLUGINClean Tool Dependency Injection with the EnvironmentPLUGIN
05Approaches to Improving AI Agent Reasoning7 материалов
Improving AI Agent Reasoning with In-Context LearningВидеоImproving AI Agent Reasoning with Up-front Planning & Chain of ThoughtВидеоThe Capability Architectural PatternPLUGINAhead of Time Planning for Improving Agent ReasoningPLUGINImproving AI Agent Reasoning with In-loop PlanningВидеоIntermediate Planning: Tracking Progress in the Agent LoopPLUGINThe Great Agent Trade-off: Ahead of Time vs. DynamicВидео