Coze Core End-to-End Practical Course — 2026 Latest Guide
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Published:
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MARCH 9, 2026
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Course Type
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Coze Platform Practice
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Target Audience
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AI developers, product managers, ops staff, tech enthusiasts, agent developers
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The course comes from Hua Zai'sCoze Core End-to-End Practical Course . It walks you from zero to fully mastering Coze. First it explains underlying logic—variables, JSON, LLMs—then dissects core nodes like workflow, plugins, selector, and loop. Then it goes deep into database operations, agent configuration, and knowledge-base setup, finishing with H5 and Web page practice.
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The course starts with understanding the Coze platform, systematically explaining how to correctly learn Coze methodology. In the underlying-logic section, it deeply analyzes variables and data structures, helping you build a solidcognitive foundation . The variables deep-dive course fully explains variables as a core concept, so you understand variables' important role in Coze workflows. The LLM-node application course focuses on how to effectively use LLMs in real projects.
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JSON data types and structures are a focus of this course; you'll learn JSON data-structure practice, JSON objects, and object arrays. In the node-deep-dive section, the course systematically explains start/end nodes, core LLM knowledge, advanced LLM knowledge (batch processing), workflow nodes, plugin nodes, and othercore components。
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. The selector-node application course goes from intro to kernel knowledge to advanced points, layer by layer. The loop-node section covers the underlying framework, array loops, intermediate variables, infinite + counted loops, continue + break loops, and more. Other core nodes—batch processing, input/output, variable aggregation, intent recognition, code nodes—are all explained in detail.
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The database section covers full CRUD—create, update, delete, query. The agent-configuration course starts from the initial Coze agent and deeply explains agent LLM prompts, skill invocation, card practice, memory, conversation experience, and multi-agent advanced features. Knowledge-base setup covers text, table, and image knowledge bases plus node practice. Finally, through H5/Web page design, Coze practice video workflows, external API plugin calls, copy secondary-creation + one-click image writing to Feishu sheets, and interior-designer agent building,practice projects , you consolidate what you've learned.
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[Basic Awareness & Underlying Logic]
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- 1.Getting to Know the Coze Platform
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- 2.Correct Coze-Learning Methodology
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- 3.Underlying Logic: Variables and Data Structures
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- 4.Variables Deep Dive and Application
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- 5.LLM Node Application
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[JSON & Data Structures]
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- 6.JSON Data Types and Structures
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- 7.JSON Data-Structure Practice
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- 8.JSON Objects and Object Arrays
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[Core Nodes Deep Dive]
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- 9.Start and End Nodes Explained
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- 10.LLM Core Knowledge
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- 11.LLM Advanced Knowledge: Batch Processing
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- 12.Workflow Nodes Explained
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- 13.Plugin Nodes Explained
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- 14.Selector Node Application Intro
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- 15.Selector Node Kernel Knowledge
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- 16.Selector Node Advanced Knowledge
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- 17.Loop Node Underlying Knowledge Framework
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[Loops & Data Processing]
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- 18.Array Loops Explained
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- 19.Loop Node: Intermediate Variables Explained
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- 20.Loop Node: Infinite and Counted Loops
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- 21.Loop Node: Continue and Break Loops
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- 22.Batch-Processing Node Explained
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- 23.Input and Output Nodes Explained
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- 24.Variable Aggregation Node Explained
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- 25.Intent-Recognition Node Explained
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- 26.Code Node Underlying Logic Explained
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[Code & Database Operations]
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- 27.Code Node: AI Programming Code
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- 28.Database: Create Data Explained
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- 29.Database: Update Data Explained
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- 30.Database: Delete Data Explained
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- 31.Database: Query Data Explained
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- 32.Database: Update Data Supplementary Knowledge
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- 33.Application-Page Build and New Nodes Explained
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[Agent Configuration & Development]
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- 34.Database Nodes Integrated Application
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- 35.Database Login/Delete/Update Nodes Build
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- 36.Initial Coze Agent
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- 37.Agent LLM Prompts Explained
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- 38.Agent Skills: Plugin and Workflow Invocation
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- 39.Agent Cards in Practice
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- 40.Agent Memory Explained
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- 41.Agent Conversation Experience Optimization
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- 42.Multi-Agent System Explained
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- 43.Multi-Agent Supplementary Knowledge
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[Knowledge-Base Build & Application]
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- 44.Knowledge-Base Concept Intro
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- 45.Text Knowledge Base Explained
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- 46.Table Knowledge Base Explained
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- 47.Image Knowledge Base Explained
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- 48.Knowledge-Base Node Practice
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[Practice Projects & Advanced Applications]
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- 49.H5 UI Page Practice Design
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- 50.H5 Login Page + Workflow Practice
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- 51.Web UI Page Practice Design
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- 52.Web Signup Page + Workflow Practice
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- 53.Coze Practice Video Workflow (Part 1)
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- 54.Coze Practice Video Workflow (Part 2)
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- 55.Coze External API Plugin Calls (Part 1)
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- 56.Coze External API Plugin Calls (Part 2)
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- 57.Copywriting Rewrite + One-Click Image Insertion into Feishu Sheets
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- 58.Decoration designer agent construction practice
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- 59.Version 2.0 Coze Latest Interface Intro
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[July 6, 2026] Updates
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🕒 Updated: July 6, 2026
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Add the following sections:
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- Coze External API Plugin Calls (Part 2)
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- Seedance 2.0 One-Click Selling Video Generation (Full Version)
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- Copywriting Rewrite + One-Click Image Insertion into Feishu Sheets
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- Decoration designer agent construction practice
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- One-Click Digital-Human Talking-Head Video
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📋 Update Key Points:
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- Deeply learn advanced Coze agent external-API calling tricks to achieve more complex data interaction and feature integration.
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- Master the Seedance 2.0 video-generation tool to quickly produce high-quality selling videos and lift content-production efficiency.
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- Learn copy secondary creation and one-click image writing to Feishu sheets for content-management and data automation.
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- Build an interior-designer agent in practice—from requirements analysis to feature implementation, fully constructing a professional-domain AI assistant.
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- Master one-click digital-human talking-head video tech to build virtual hosts at low cost, suited to short-video and live scenarios.
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💡 Learning Tips:The content of the tutorial is based on industry practice at the time of release, and it is recommended to combine the latest rules of the current platform when learning.
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