FOUNDATIONS
Introduction to Artificial Intelligence
A scenario-based course connecting AI concepts, data thinking, model limitations, and the social consequences of intelligent systems.
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.
01
Course experiences
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.