К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
Building AI-Powered Chatbots with Flowise · LearnSpace
Назад в каталог
courseraПрограммирование

Building AI-Powered Chatbots with Flowise

Курс от Edureka
Начальный≈ 5.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

No-code chatbot development is becoming one of the fastest ways to build intelligent conversational applications without writing complex code. In this hands-on course, you’ll learn how to use Flowise, a visual no-code AI workflow platform that helps you build LLM-powered chatbots, configure conversational flows, add memory, connect knowledge bases, integrate tools, and deploy chatbot experiences through an intuitive drag-and-drop interface. You’ll begin by understanding the foundations of modern chatbots, including how rule-based chatbots evolved into LLM-powered conversational systems. You’ll explore how AI chatbots work, how conversations are structured, and how Flowise uses nodes, chatflows, prompts, memory, knowledge, and tools to create chatbot workflows. Then, you’ll move through practical exercises—from setting up the Flowise workspace and configuring model providers to building your first conversational bot and sharing a working chatbot flow. As the course progresses, you’ll learn how to design better chatbot behavior using system prompts, reusable prompt templates, memory, edge-case handling, fallbacks, and guardrails. You’ll also build knowledge-aware chatbots using RAG workflows, document preparation, chunking, embeddings, vector stores, retrieval tuning, and rerankers. In the final part of the course, you’ll extend chatbot capabilities with tool-calling, connect calculator, search, and API tools, deploy chatbots using embed widgets and shareable links, and review monitoring, analytics, responsible AI, and prompt injection safety practices. By the end of this course, you will be able to: -Understand the core concepts of chatbot development, including LLM-powered conversations, Flowise chatflows, prompts, memory, knowledge bases, tools, and RAG. -Build chatbot workflows in Flowise by configuring model providers, connecting LLMs, managing credentials, and creating conversational experiences. -Design effective chatbot behaviour using prompt engineering, reusable prompt templates, conversation memory, guardrails, and fallback strategies. -Create knowledge-aware and tool-enabled chatbots by implementing RAG pipelines, vector stores, retrieval optimisation, and external tool integrations. -Deploy, monitor, and improve chatbots using analytics while applying responsible AI practices and mitigating prompt injection risks. This course is designed for beginners, software developers, AI enthusiasts, automation professionals, business analysts, product teams, support teams, and learners who want to build AI-powered chatbots without writing full application code. If you are new to Flowise, chatbot design, no-code AI tools, or knowledge-aware conversational systems, this course provides a practical starting point. Learners should have basic familiarity with AI tools and an interest in building chatbot-based applications. Prior coding experience is helpful but not required. Familiarity with prompts, documents, APIs, and basic web tools will make the hands-on exercises easier to follow. Enroll now and learn how to design, build, test, deploy, and improve AI chatbots with Flowise. Start with chatbot foundations, practice with real no-code chatbot workflows, and build confidence using visual AI development as part of modern conversational application building.

Навыки, которые вы освоите

Prompt EngineeringRetrieval-Augmented GenerationContext ManagementLarge Language ModelingKnowledge TransferJSONVector DatabasesAI SecurityPrototypingGenerative AI AgentsAI PersonalizationAgentic WorkflowsSystems ArchitectureEmbeddingsApplication DeploymentContinuous MonitoringPrompt PatternsGenerative AITest ToolsArtificial Intelligence

Программа курса

3 модулей · 44 учебных материалов

01Chatbot Foundations and First Flowise Chatbot16 материалов
Course IntroductionВидеоCourse Syllabus: Building AI-Powered Chatbots with FlowiseЧтениеThe Evolution of Chatbots: Rule-Based to LLM-PoweredВидеоHow LLM Chatbots Work: Anatomy of a ConversationВидео

Учитесь у экспертов

Edureka

Преподаватель курса

Building AI-Powered Chatbots with Flowise
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 5.5 ч

3 модулей

Язык: Английский

Часть программы вашего университета
Hands-On: Getting Started with Flowise Workspace and Visual BuilderВидео
LLM Chatbot Architecture Reference GuideЧтение
Hands-On: Touring the Flowise Canvas, Nodes, and ChatflowsВидео
Chatbot Foundations and Flowise Workspace CheckЗадание
Core Components of AI Chatbots: Prompts, Memory, Knowledge, and ToolsВидео
Anatomy of a Flowise Workflow: Nodes, Chains, and Data FlowВидео
Hands-On: Configuring Model Providers and Connecting Your First LLMВидео
Flowise Setup and Credential Configuration ChecklistЧтение
Key Flowise Components and TerminologyЧтение
Hands-On: Building, Testing, and Sharing Your First Conversational ChatbotВидео
Chatbot Use Cases and Design Planning GuideЧтение
Module 1 Assesment: Chatbot Foundations and Flowise Workspace CheckЗадание
02Prompt Design, Memory, and Knowledge-Aware Chatbots15 материалов
System Prompts: Shaping Chatbot Persona and BehaviorВидеоHands-On: Applying Prompt Engineering Patterns for ChatbotsВидеоHands-On: Creating Reusable Prompt Templates in FlowiseВидеоPrompt Engineering Framework Cheat SheetЧтениеHands-On: Adding Conversation Memory in FlowiseВидеоHands-On: Handling Edge Cases, Fallbacks, and GuardrailsВидеоPrompting, Memory, and Guardrails CheckЗаданиеWhy RAG Matters for Knowledge-Aware ChatbotsВидеоHands-On: Preparing Documents for a Chatbot Knowledge BaseВидеоHands on: Documents Retrieval with Embeddings and Vector StoreВидеоHands-On: Building a Document-Trained RAG ChatbotВидеоHands-On: Improving Retrieval Quality with Rerankers and TuningВидеоRetrieval Quality and RAG Troubleshooting ChecklistЧтениеBuilding Intelligent Chatbots with Flowise: Prompt Engineering, Memory, and RAGDIALOGUEModule 2 Assessment: Prompt Design, Memory, and Knowledge-Aware ChatbotsЗадание
03Tool-Using Chatbots, Deployment, and Operations13 материалов
Giving Chatbots Tools: Tool-Calling in FlowiseВидеоHands-On: Adding Tool-Calling to a Flowise ChatbotВидеоHands-On: Connecting Calculator, Search, and API ToolsВидеоTool-Using Chatbot Design GuideЧтениеTool-Using Chatbot CheckЗаданиеHands-On: Deploying Your Chatbot with Embed Widget and Shareable LinkВидеоChatbot Deployment and API Sharing ChecklistЧтениеHands-On: Monitoring, Analytics, and Iterating After LaunchВидеоResponsible AI, Prompt Injection, and Chatbot Safety GuideЧтениеInterview: Designing a Production-Ready AI Chatbot with FlowiseDIALOGUEPractice Project: Building a Production-Ready AI Customer Support Chatbot with FlowiseЧтениеFinal Course Assessment: Building AI-Powered Chatbots with FlowiseЗаданиеCourse SummaryВидео