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Agentic AI Foundations: Architectures & Adaptation Strategy · LearnSpace
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Agentic AI Foundations: Architectures & Adaptation Strategy

Курс от Packt
Средний≈ 5.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Explore the foundational concepts, architectures, and adaptation strategies for building agentic AI systems in enterprise environments. Learn how to select, deploy, and adapt large language models to create robust, agent-ready solutions. This course introduces the landscape of GenAI in the enterprise, focusing on the essential architectural features and challenges of agentic AI systems. Learners will gain practical knowledge on selecting and deploying large language models, understanding adaptation techniques such as retrieval-augmented generation (RAG) and fine-tuning, and designing hierarchical agentic architectures for business process automation. By the end of the course, participants will be equipped to make informed decisions about model selection, adaptation, and deployment for agentic AI applications. The course blends conceptual overviews with real-world case studies and technical guidance, providing a structured pathway from foundational principles to practical implementation. Learners will engage with frameworks, tradeoff analyses, and step-by-step examples to build a strong foundation in agentic AI. This course is part one of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Agentic Architectural Patterns for Building Multi-Agent Systems, by Dr. Ali Arsanjani and Juan Pablo Bustos. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Навыки, которые вы освоите

Agentic systemsGenerative AI AgentsModel DeploymentTool CallingContext EngineeringAgentic WorkflowsArtificial Intelligence and Machine Learning (AI/ML)Fine-tuningAI OrchestrationData ScienceGenerative AIGenerative Model ArchitecturesPrompt EngineeringRetrieval-Augmented GenerationAI WorkflowsLarge Language ModelingLLM ApplicationLangChainData ArchitectureAI Security

Программа курса

4 модулей · 49 учебных материалов

01GenAI in the Enterprise: Landscape, Maturity, and Agent Focus9 материалов

Navigating GenAI Adoption: From Business Use Cases to Agentic Architectures

OverviewВидеоIntroductionЧтениеOverview of business applicationsЧтениеIntroducing agentic AI systemsЧтение

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Packt - Course Instructors

Преподаватель курса

Agentic AI Foundations: Architectures & Adaptation Strategy
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Обучение на Coursera

≈ 5.9 ч

4 модулей

Язык: Английский

Часть программы вашего университета
Recommending GenAI Applications for Business TransformationDIALOGUE
Key architectural featuresЧтение
The new agentic stackЧтение
Challenges hindering production-grade GenAIЧтение
GenAI in the Enterprise: Strategic Frameworks and ImplementationЗадание
02Agent-Ready LLMs: Selection, Deployment, and Adaptation15 материалов

Building and Optimizing LLM Foundations for Agentic AI

OverviewВидеоIntroductionЧтениеModel selection: choosing the right foundationЧтениеContext window sizeЧтениеModel size and specialization for agentsЧтениеNative support for tool use and function callingЧтениеAdaptability and fine-tuning potentialЧтениеSelecting Agent-Ready LLMs: Key Technical CriteriaDIALOGUEOther key selection considerationsЧтениеDeployment and performance optimization for agentsЧтениеPerformance optimization strategiesЧтениеSecurity considerations in LLM deployment for agentsЧтениеAgentOps: managing LLMs in agentic systemsЧтениеSummaryЧтениеAgent-Ready LLMs: Key Concepts and Design ChoicesЗадание
03The Spectrum of LLM Adaptation for Agents: RAG to Fine-tuning15 материалов

Mastering LLM Adaptation: From Retrieval to Fine-Tuning in Agentic AI

OverviewВидеоIntroductionЧтениеAnother maturity model for agentic AIЧтениеA hierarchical agentic architecture for business process automationЧтениеThe hierarchical structure: orchestrators and specialistsЧтениеContextual enhancement: stage 1, enhancement with RAGЧтениеFinancial analyst agent leveraging RAG for timely market insightsЧтениеRecommending an LLM Adaptation Strategy for Business Process AutomationDIALOGUECompliance agent ensuring adherence with RAG in transaction monitoringЧтениеAnalyzing the scenariosЧтениеThe spectrum of tuning: parameter-efficient fine-tuning to full fine-tuningЧтениеIn-context learning for agent adaptationЧтениеEnd-to-end example: Product feedback analyzer agent with ICLЧтениеGrounding the model outputЧтениеLLM Adaptation for Agent SystemsЗадание
04Agentic AI Architecture: Components and Interactions10 материалов

Building Intelligent Agents: Architecture, Context, and Real-World Integration

OverviewВидеоIntroductionЧтениеAI agentsЧтениеCase study: Travel Planning AgentЧтениеExplaining Agentic AI System ComponentsDIALOGUEData stores and environment context for agentsЧтениеAgent interaction models and key featuresЧтениеTechnical considerations for agentic architecturesЧтениеAgentic AI System FundamentalsЗаданиеFoundations of Agentic AI: Architectures and Adaptation Strategies Final AssessmentЗадание