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CrewAI Flows and Monitoring · LearnSpace
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courseraПрограммирование

CrewAI Flows and Monitoring

Курс от Edureka
Средний≈ 9.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This program introduces you to CrewAI Flows and Monitoring, designed for developers and AI professionals who want to build scalable, reliable, and production-ready multi-agent systems. You’ll begin by mastering the foundations of workflow orchestration using CrewAI Flows, learning how to design event-driven pipelines with @start, @listen, and @router to control execution, manage state, and implement dynamic routing. Next, you’ll focus on building reliable agent systems by integrating guardrails and human-in-the-loop workflows. You’ll learn how to validate outputs using TaskGuardrails, apply LLM-as-a-judge techniques for quality evaluation, and design workflows that incorporate human feedback using the @human_feedback decorator. Through hands-on demonstrations, you’ll ensure your systems produce accurate, controlled, and trustworthy outputs. As you progress, you’ll explore multi-crew orchestration and advanced workflow design patterns. You’ll learn how to structure scalable systems by distributing responsibilities across multiple crews and optimizing execution using hybrid sequential and parallel workflows. You’ll also gain practical experience in monitoring and debugging agent systems using observability tools like LangSmith and AgentOps. By the end of the program, you will be able to: - Explain the principles of event-driven workflows and CrewAI flow orchestration. - Apply guardrails and validation strategies to ensure reliable agent outputs. - Design human-in-the-loop workflows to balance automation and oversight. - Build scalable multi-crew architectures for complex agent systems. - Optimize workflow execution using hybrid sequential and parallel patterns. - Monitor and debug production systems using observability tools and performance metrics. This program is ideal for developers, AI engineers, and technical professionals looking to build production-grade agent systems using CrewAI. A basic understanding of Python programming and familiarity with AI concepts will help you get the most out of this course. Learners will need a reliable internet connection, a modern web browser, and access to Python development tools. The course uses CrewAI and related observability tools, which do not require specialized hardware. Basic knowledge of Python and agent-based AI systems is recommended. Join us and learn how to design intelligent workflows, build reliable agent systems, and deploy scalable AI solutions powered by CrewAI.

Навыки, которые вы освоите

AI WorkflowsCrewAIScalabilityAI OrchestrationEvent-Driven ProgrammingHuman FactorsData ValidationAgentic WorkflowsWorkflow ManagementBuild ToolsHuman Centered DesignSystem MonitoringLLM ApplicationPython ProgrammingMaintainabilityAgentic systemsDebuggingGenerative AI AgentsModel EvaluationAI Integrations

Программа курса

4 модулей · 61 учебных материалов

01Workflow Orchestration with CrewAI Flows21 материалов

Introduction to CrewAI Flows and Event Driven Workflows

Specialization IntroductionВидеоCourse IntroductionВидеоCourse SyllabusЧтениеFoundation of CrewAI Flows and Event-Driven WorkflowВидео

Учитесь у экспертов

Edureka

Преподаватель курса

CrewAI Flows and Monitoring
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в новой вкладке

Обучение на Coursera

≈ 9.6 ч

4 модулей

Язык: Английский

Часть программы вашего университета
Demonstration: Exploring the CrewAI Flow Project StructureВидео
Demonstration: Building and Launching a Flow with @start decoratorВидео
Flow Architecture Design PrinciplesЧтение
Knowledge Check: Introduction to CrewAI Flows and Event Driven WorkflowsЗадание

Flow Fundamentals and State Management

Designing Flow Based Agent WorkflowsВидеоDemonstration: Triggering Sequential Steps with the @listen DecoratorВидеоDemonstration: Running Parallel Steps with Multiple @listen DecoratorsВидеоFlow Development Best PracticesЧтениеKnowledge Check: Flow Fundamentals and State ManagementЗадание

Advanced Flow Routing and Workflow Patterns

Conditional Routing with CrewAI FlowsВидеоDemonstration: Implementing Conditional Branching with the @routerВидеоDemonstration: Integrating Multiple Crews into a Complete Flow PipelineВидеоDesigning Efficient and Scalable Flow Architectures in CrewAIЧтениеKnowledge Check: Advanced Flow Routing and Workflow PatternsЗадание

Module Wrap-Up and Assessment

Module Summary: Workflow Orchestration with CrewAI FlowsЧтениеKnowledge Check: Workflow Orchestration with CrewAI FlowsЗаданиеDesigning an Event-Driven Workflow with CrewAI FlowsDIALOGUE
02Guardrails and Human-in-the-Loop Workflows18 материалов

Implementing AI Guardrails for Agent Systems

Guardrails for Reliable AI Agent SystemsВидеоDemonstration: Setting Up the TalentFlow CrewAI PipelineВидеоDemonstration: Validating Agent Outputs with GuardrailsВидеоBuilding Trustworthy Agent Systems with GuardrailsЧтениеKnowledge Check: Implementing AI Guardrails for Agent SystemsЗадание

Advanced Guardrail Design Patterns

LLM as Judge for Agent Output EvaluationВидеоDemonstration: Output Quality Validation and Scoring using LLMВидеоDemonstration: Implementing Hallucination Detection GuardrailsВидеоImplementing Guardrails in Agent WorkflowsЧтениеKnowledge Check: Advanced Guardrail Design PatternsЗадание

Human in the Loop Agent Workflows

Human in the Loop Architecture for AI AgentsВидеоDemonstration: Implementing the @human_feedback DecoratorВидеоDemonstration: Building a Complete Human Approval WorkflowВидеоHuman AI Collaboration PatternsЧтениеKnowledge Check: Human in the Loop Agent WorkflowsЗадание

Module Wrap-Up and Assessment

Module Summary: Guardrails and Human-in-the-Loop WorkflowЧтениеKnowledge Check: Guardrails and Human-in-the-Loop WorkflowЗаданиеDesigning Reliable and Controlled Agent Workflows with GuardrailsDIALOGUE
03Multi-Crew Orchestration and Observability16 материалов

Designing Multi-Crew AI Systems

Multi Crew AI System ArchitectureВидеоDemonstration: Embedding Multiple Crews Within FlowsВидеоScalable Multi-Crew Architectures in CrewAIЧтениеKnowledge Check: Designing Multi-Crew AI SystemsЗадание

Building Complex Multi-Agent Workflows

Hybrid Sequential and Parallel Agent WorkflowsВидеоDemonstration: Building Project Planning Multi Crew SystemsВидеоScalable Workflow Architecture PatternsЧтениеKnowledge Check: Building Complex Multi-Agent WorkflowsЗадание

Monitoring and Securing Microsoft Warehouse

Observability for Production AI AgentsВидеоMonitoring and Debugging Agents with LangSmithВидеоDemonstration: Integrating LangSmith for Agent MonitoringВидеоObservability Best Practices and Tool ComparisonЧтениеKnowledge Check: Observability and Monitoring for AI AgentsЗадание

Module Wrap-Up and Assessment

Module Summary: Multi-Crew Orchestration and ObservabilityЧтениеKnowledge Check: Multi-Crew Orchestration and ObservabilityЗаданиеDesigning and Monitoring Scalable Multi-Crew WorkflowsDIALOGUE
04Course Wrap-Up and Assessment6 материалов

Course Conclusion

Reflecting on Your CrewAI JourneyDIALOGUEPractice Project: Building a CrewAI Incident Response SystemЧтениеKnowledge Check: Building Scalable AI Agent Systems with CrewAI FlowsЗаданиеDesigning a Scalable and Observable Multi-Crew Workflow System with CrewAIЗаданиеCourse SummaryВидеоDescribe Your Learning JourneyОбсуждение