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Implementation of GenAI Agents · LearnSpace
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Implementation of GenAI Agents

Курс от Coursera
Средний≈ 4.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course offers a fast-paced, hands-on introduction to the world of AI agents, perfect for aspiring AI architects and innovators. In just 75 minutes, you'll develop the skills to build AI agents that can understand, reason, and act in real-world scenarios. With a focus on efficiency and practical development, you'll dive straight into coding while gaining techniques that are scalable for future projects. This course is crafted for software developers, AI engineers, data scientists, and data and business analysts who are keen to implement AI in real-world scenarios. If you're interested in expanding your technical skills and gaining hands-on experience with AI agent development, this is the perfect starting point. Whether you're aiming to enhance existing applications, explore AI-powered solutions, or bring new ideas to life, this course equips you with essential skills for AI-driven innovation. This course is designed to be accessible to learners with a foundational understanding of Python programming and a general awareness of AI concepts; advanced AI expertise is not required. To participate fully, you’ll need a computer with a reliable internet connection, as the course involves hands-on coding exercises and interactive problem-solving. An openness to practical, step-by-step learning and real-world application is key, as this course emphasizes a mix of theory and immediate implementation. By the end of this course, learners will have the skills to apply core principles of AI agent architecture, enabling them to design and implement a basic agent system. You'll gain the capability to construct an efficient development environment for building and testing your AI agents, facilitating smooth workflows and testing processes. Additionally, you’ll develop a fully functional AI agent using frameworks like LangChain or AutoGen and learn to evaluate and optimize its performance through advanced feature integration, enhancing your agent’s effectiveness and adaptability in real-world applications.

Навыки, которые вы освоите

Performance TuningGenerative AI AgentsAgentic WorkflowsLangChainModel OptimizationModel EvaluationArtificial IntelligenceAI literacyAI OrchestrationAgentic systemsDesignLLM ApplicationDevelopment EnvironmentGenerative AIScalability

Программа курса

1 модулей · 35 учебных материалов

01Implementation of GenAI Agents35 материалов

Lesson 1: Designing AI Agent Architecture

Welcome to the CourseDIALOGUEWelcome to the Course: Course Overview ЧтениеIntroduction to the Course & Meet Your InstructorВидеоFundamentals of AI Agent Architecture Видео

Учитесь у экспертов

Ritesh Vajariya

Advisor | Leader | Speaker |Author

Starweaver

Global Leaders in Professional & Technology Education

Implementation of GenAI Agents
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Обучение на Coursera

≈ 4.7 ч

1 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
Architecting Your AI Agent's Blueprint Видео
Designing Your Agent's Decision-Making Core Видео
Mapping Your Agent's Interaction Flow Видео
Hands On Learning (HOL): Designing Your Own AI Agent ArchitectureЧтение
Structuring Your Agent's Knowledge Base Видео
AI Agent Architectures: From Theory to Practice Чтение
Architectural Thinking DialogueDIALOGUE
Enhancing AI Assistants with an Innovative ComponentОбсуждение

Lesson 2: Developing a Functional AI Agent

Constructing Your AI Development Lab ВидеоIntegrating AI Frameworks and Libraries ВидеоImplementing Your Agent with LangChain/AutoGen ВидеоCoding Core Agent Functionalities ВидеоHands On Learning (HOL): Implementing Core AI Agent FunctionalitiesЧтениеBest Practices in AI Development Environments and Framework Selection ЧтениеTechnical Deep-Dive DialogueDIALOGUEImpact of Knowledge Base Technology on AI Agent PerformanceОбсуждение

Lesson 3: Optimizing AI Agent Performance

Evaluating Your AI Agent's Performance ВидеоEnhancing Your Agent with Memory Capabilities ВидеоOptimizing Your Agent with Advanced Tools ВидеоCutting-Edge Techniques in AI Agent OptimizationЧтениеImpact of AI agents on Research and LearningDIALOGUE(Optional) Optimizing Research through Multi-Source and Parallel ProcessingОбсуждениеFine-Tuning Your AI Assistant for Peak Performance ВидеоHands On Learning (HOL): Optimizing and Evaluating Your AI Research AssistantЧтениеCongratulations and Continuous Learning JourneyВидеоGenAI-Empowered Personal Assistant Development ReportЗаданиеImplementation of GenAI AgentsЗадание

[Optional] Practice for the Real World

Put Your Skills to the Test — Without the Stakes!ЧтениеPresenting Your AI Agent Implementation ProposalDIALOGUEDiagnosing a Performance Bottleneck in Your AI Research AssistantDIALOGUEQuick Pulse Check : Role-playsЗадание