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Building AI Agents for Complex Tasks · LearnSpace
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Building AI Agents for Complex Tasks

Курс от Coursera
Средний≈ 5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Building AI Agents for Complex Tasks is an intermediate-level course designed to equip learners with the skills to design, build, and evaluate intelligent agents that operate autonomously across dynamic, multi-step environments. Moving beyond simple chatbot flows, this course introduces learners to agent architectures that perceive context, make decisions, integrate tools, and recover from failure. Through hands-on labs, interactive video walkthroughs, and real-world case studies—including Alexa, BabyAGI, and AlphaCode—learners will explore agent types, design patterns, tool orchestration, memory management, and behavior evaluation. They'll gain practical experience using modern frameworks like LangChain and Rasa to construct agents for use cases such as research automation, virtual assistants, and decision-making bots. By the end of the course, learners will have built and tested their own intelligent agent and developed the foundational skills to implement agent-based AI systems that can adapt, reason, and act in real-world applications.

Навыки, которые вы освоите

Model EvaluationTool CallingDebuggingAI OrchestrationDevelopment TestingArtificial IntelligenceGenerative AI AgentsAgentic WorkflowsMemory ManagementLLM ApplicationLangChainAI WorkflowsAgentic systems

Программа курса

3 модулей · 30 учебных материалов

01Lesson 1: Explore AI Agents – Concepts, Types, and Foundations7 материалов
Welcome to the Course: Course OverviewЧтениеIntroduction and WelcomeВидеоHow AI Agents Perceive the World Around ThemВидеоReactive vs. Deliberative Agents in the Real WorldВидео

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Преподаватель курса

Building AI Agents for Complex Tasks
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Обучение откроется на Coursera
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Обучение на Coursera

≈ 5 ч

3 модулей

Язык: Английский

Часть программы вашего университета
Rasa vs. AutoGPT – Choosing the Right Agent ModelВидео
HOL: Practice Classifying Agent Types in Real-World Use CasesЗадание
Justify Your Agent ClassificationsDIALOGUE
02Lesson 2: Build Intelligent Agents Using Perception, Planning, and Tools8 материалов
How Intelligent Agents Turn Input into ImpactВидеоLangChain and Rasa: Agent Workflows and APIsЧтениеHOL: Build a Simple Multi-Step Agent Using LangChain or RasaЗаданиеReflecting on Your Multi-Step Agent BuildDIALOGUEDesigning Action Loops and Memory ModulesВидеоAlexa Multi-Intent Flow and Long Chain Tool UseВидеоHOL: Intelligent Agent LabЗаданиеDebug and Refine Agent Architecture for a Given Use CaseDIALOGUE
03Lesson 3: Evaluate and Optimize Agent Behavior in Dynamic Environments15 материалов

Evaluate and Optimize Agent Behavior in Dynamic Environments

Is Your Agent Really Working? ВидеоEdge Cases, Loops, and Failure Modes in Agent SystemsЧтениеAgent Behavior Breakdown: Debugging and TestingВидеоHOL: Diagnose and Improve an Agent’s Behavior Using Logs and ExamplesЗаданиеBabyAGI, AlphaCode: Improving Agent Performance Over TimeВидеоHOL: Diagnose and Improve an Agent’s Behavior Using Logs and Edge CasesЗаданиеPressure Test Your Own Agent DesignDIALOGUECongratulations and Continuous Learning JourneyВидеоProject: Design and Deploy a Real-World AI AgentЗаданиеAssessmentЗадание

[Optional] Practice for the Real World

Put Your Skills to the Test — Without the Stakes!ЧтениеPair Programming: Designing a Resilient AI AgentDIALOGUEThe Architecture Debate: Building Your AI AgentDIALOGUEPitching AI Capabilities to Your ManagerDIALOGUEQuick Pulse Check : Role-playsЗадание