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Building Autonomous AI Agents · LearnSpace
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Building Autonomous AI Agents

Курс от Edureka
Начальный≈ 7.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Artificial intelligence is rapidly advancing from simple automation to systems that can reason, plan, and act on their own. Building Autonomous AI Agents is a hands-on, practice-driven course that walks you through the end-to-end process of designing, developing, and deploying intelligent agents capable of independent decision-making. You’ll work with leading agent frameworks—including LangChain, Autogen, and AgentOps—and learn how to integrate models, tools, and APIs to build dynamic multi-agent ecosystems. Through guided demonstrations and structured labs, you’ll implement core agent components such as memory, tool use, planning modules, and goal-driven workflows, ultimately building a fully functional autonomous agent. The course also emphasizes safety, evaluation, and alignment practices to ensure that agents operate transparently, ethically, and reliably in real-world settings. By the end of this course, you will be able to: • Understand core agent architectures, memory types, and planning strategies. • Build agents using frameworks like LangChain, CrewAI, Autogen, and AgentOps. • Connect models, APIs, and external tools into cohesive multi-agent systems. • Implement goal-driven workflows with monitoring, evaluation, and safety controls. • Deploy production-ready autonomous agents capable of operating reliably in real environments. This course is ideal for AI developers, data scientists, software engineers, and technology professionals transitioning from basic prompt engineering to building fully autonomous systems. A foundational understanding of Python, APIs, and basic AI concepts is recommended, though all frameworks are introduced from scratch. Join us to master the tools and techniques that power the next generation of AI systems that can think, act, and collaborate with minimal human intervention.

Навыки, которые вы освоите

Agentic systemsLangGraphRetrieval-Augmented GenerationAI WorkflowsAI OrchestrationPrompt EngineeringAgentic WorkflowsVerification And ValidationLangChainLLM ApplicationAI IntegrationsCrewAILarge Language ModelingDecision IntelligenceSystems IntegrationGenerative AI AgentsMemory ManagementArtificial Intelligence and Machine Learning (AI/ML)Responsible AITool Calling

Программа курса

4 модулей · 67 учебных материалов

01The Agentic Foundation (ReAct & Tool Use)25 материалов

Foundations of Agentic AI

Specialization IntroductionВидеоCourse IntroductionВидеоCourse Outline: Building Autonomous AI Agents ЧтениеPython Prerequisites for Agentic AI DevelopmentВидео

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Edureka

Преподаватель курса

Building Autonomous AI Agents
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Обучение на Coursera

≈ 7.9 ч

4 модулей

Язык: Английский

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

Часть программы вашего университета
Setting Up Environment for AI AgentsВидео
Understanding the ReAct Reasoning LoopЧтение
The Rise of Autonomous Agents and the SDR Case StudyВидео
AI Agent ProtocolsВидео
Agent vs. LLM Why ReAct is the Next Generation of PromptingВидео
Hands-On: Setting Up the Agent Development Environment (Python & Libraries)Видео
Foundations of Agentic AIЧтение
Practice Quiz: Foundations of Agentic AIЗадание

Tool Development and Action

Hands-On: Anatomy of a Tool (Part 1) Defining Functions & DocstringsВидеоHands-On: Anatomy of a Tool (Part 2) Using Pydantic for Structured InputВидеоHands-On: Building Your First Research Tool (Web Search Integration)ВидеоTool Development and ActionЧтениеPractice Quiz: Tool Development and ActionЗадание

ReAct Implementation & Memory

The Core ReAct Loop: Thought, Action, Observation in CodeВидеоHands-On: Prompt Engineering for Reasoning How to Get Better Tool UseВидеоHands-On: Implementing State Giving Your Agent Short-Term MemoryВидеоHands-On: Milestone Deploying the Researcher Agent (Tool & Memory Test)ВидеоReAct Implementation & MemoryЧтениеPractice Quiz: ReAct Implementation & MemoryЗадание

Module Wrap-Up and Assessment

Summary: The Agentic Foundation (ReAct & Tool Use)ЧтениеKnowledge Check: The Agentic Foundation (ReAct & Tool Use)Задание
02Context, Knowledge, and Grounding (RAG)18 материалов

RAG Architecture and Data Ingestion with TypeScript

RAG TheoryВидеоHands-On: Data Preparation Loading & Splitting the Internal Sales PlaybookВидеоHands-On: Text Embeddings How to Convert Documents to Vector SpaceВидеоHands-On: Building the Vector Database & Indexing the Sales PlaybookВидеоRAG Architecture and Data IngestionЧтениеPractice Quiz: RAG Architecture and Data IngestionЗадание

Tool Integration and Actuators

Hands-On: Creating the RAG Retrieval Tool (retrieve_playbook)ВидеоHands-On: Connecting to the CRM Defining the Actuator Tool (log_activity)ВидеоHands-On: LLM Decisioning When to Use the Web Tool vs. the RAG ToolВидеоTool Integration and ActuatorsЧтениеPractice Quiz: Tool Integration and ActuatorsЗадание

Strategy-Grounded Drafting

The Multi-Step Chain: Sequencing Research, RAG, and DraftingВидеоHands-On: Prompting for Grounding and Forcing the Agent to Cite the PlaybookВидеоHands-On: The Strategy-Grounded Draft Agent (Full Output Test)ВидеоStrategy-Grounded DraftingЧтениеPractice Quiz: Strategy-Grounded DraftingЗадание

Module Wrap-Up and Assessment

Summary: Context, Knowledge, and Grounding (RAG)ЧтениеKnowledge Check: Context, Knowledge, and Grounding (RAG)Задание
03Orchestration, Validation, and Deployment (LangGraph)19 материалов

Building the State Machine

Graph Theory and MotivationВидеоAnatomy of a Graph: Nodes, Edges, and Defining Graph StateВидеоHands-On: Mapping the SDR Workflow Designing the Full Execution GraphВидеоBuilding the State MachineЧтениеPractice Quiz: Building the State MachineЗадание

Advanced Control and Self-Correction

Hands-On: Building the Validation Node Creating the LLM-as-a-JudgeВидеоHands-On: Implementing the Reflection Loop Routing for Self-CorrectionВидеоHands-On: Conditional Edges and the Logic of Decision-Making in the GraphВидеоHands-On: Integrating Manual Approval into the WorkflowВидеоAdvanced Control and Self-CorrectionЧтениеPractice Quiz: Advanced Control and Self-CorrectionЗадание

Productionizing the Agent

Hands-On: Finalizing the Actuator and Ensuring Atomic CRM LoggingВидеоHands-On: Packaging the Agent as a RESTful API with FastAPIВидеоHands-On: Monitoring, Scaling, and Advanced Multi-Agent SystemsВидеоProductionizing the AgentЧтениеPractice Quiz: Productionizing the AgentЗадание

Module Wrap-Up

Summary: Orchestration, Validation, and Deployment (LangGraph)ЧтениеAgentic Workflow DebuggingDIALOGUEKnowledge Check: Orchestration, Validation, and Deployment (LangGraph)Задание
04Course Wrap-Up and Assessment5 материалов

Course Wrap-up and Assessments

Course SummaryВидеоPractice Project: Single Agent Response ModelЧтениеThe Final Check-In: Turning AI Agent Knowledge into ActionDIALOGUEKnowledge Assistant Agent - Scenario AssignmentЗаданиеEnd Course Knowledge Check: Building Autonomous AI AgentsЗадание