University Teaching · 90 minutes
GraphRAG & Multimodal Knowledge Graphs
22 editable slides with evidence mapping, image–text alignment, transfer activities and teaching packages in both languages.
Explore collection ↗TEACHING
Teaching AI through real questions, real data, and reflective practice.
Course design for applied learners—combining conceptual clarity, hands-on tools, and responsible judgment.
The Introduction to Artificial Intelligence course is designed for students outside computer science. It begins with practical questions, uses hospitality and service scenarios, and treats AI literacy as both technical understanding and the capacity to make responsible decisions.
WORKBUDDY EXPERT TEAM · CHAPTER TO GRAPH
Knowledge Graph Teaching Workbench
Prepare a chapter task package, run it with the Knowledge Graph Expert Team in your own WorkBuddy, and import the result for evidence review, teaching, graph analysis, and export. The interface is in Chinese.
ONLINE COURSE · CHINESE & ENGLISH
Introduction to AI · Interactive Learning
Explore seven chapters, from AI foundations to generative AI, ethics, and learning, with hands-on demos of linear regression, neural networks, and K-means clustering.
AUTUMN 2026 · 16 SESSIONS · 32 ACADEMIC HOURS
Introduction to AI and Its Applications in Hotel Management
Follow the ABC Smart Hotel case through Python, data analysis, machine learning, visualization, WorkBuddy agents, and AI governance. The complete bilingual course includes interactive experiments, instant quizzes, and project checks.
COURSE KNOWLEDGE GRAPH · CONCEPTS & APPLICATIONS
Introduction to AI: Concepts and Connections
Explore how data, machine learning, large language models, and agents connect, with hotel management examples to aid understanding. Browse by lesson, search a concept, or follow its relationships back to the course source.
01
Course experiences
FOUNDATIONS
Introduction to Artificial Intelligence
A scenario-based course connecting AI concepts, data thinking, model limitations, and the social consequences of intelligent systems.
VISUALIZATION
Seeing patterns in hospitality data
Interactive exercises help students turn operational data into interpretable visual evidence.
MODELING
Clustering and regression without black-box thinking
Learners compare model outputs, assumptions, and decision consequences in accessible applied contexts.
LANGUAGE
Hotel-review analysis
Natural-language processing becomes a way to examine customer experience, negative signals, bias, and interpretation.
02
Learning support
TEACHER-GOVERNED
Xiaojiu AI Learning Coach · V3.0
A course companion designed to scaffold thinking, ask productive follow-up questions, and redirect students to evidence—while keeping assessment and final judgment with the teacher.
03
Teaching principles
01
Begin with a consequential problem
Tools enter only after the learning question and evidence needs are clear.
02
Make model limits visible
Students examine assumptions, uncertainty, error, and the responsibilities of interpretation.
03
Keep reflection inside the workflow
Learning artifacts include not only outputs, but also reasoning, revision, and responsible-use decisions.