AI x Urban Net Zero: Green Energy Fitness & Cycling Policy Practice
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Program Overview
Program Overview
The program in question appears to be a micro-credit course focused on Artificial Intelligence (AI) applications, specifically designed around the theme of "AI x Urban Net Zero: Green Energy Fitness & Cycling Policy Practice." This course is part of a broader curriculum that aims to integrate AI, data modeling, and policy-making to address urban sustainability challenges.
Course Description
The course is based on the latest research framework by Cheng (2025) and combines three major trends: "Net Zero Transition," "Preventive Medicine," and "AI Data Decision-making." It aims to go beyond the conventional use of YouBike as a commuting tool by exploring the possibility of transforming public bicycles into "mini green power generation stations" using AI tools.
Learning Objectives
Through project-based learning, students will simulate the role of urban planners and design new bike stations that combine "Revive" reclining charging cars with solar canopies for "transportation vulnerable groups" (the elderly and obese). By doing so, students will learn "Low-Code, High-Impact" strategic thinking, utilizing generative AI (ChatGPT) to establish models, quantify the specific contributions of bicycles to psychological health and grid resilience, and produce sustainable policy proposals that can withstand AI simulation inquiries.
Course Goals
The course aims to cultivate students' ability to combine behavioral economics and AI data modeling. Upon completion, students will be able to integrate SDG health and energy indicators, use Excel DAX to establish a "health and carbon reduction" monetization avoidance cost model, and conduct data storytelling using Power BI to design gamified reward policies. Ultimately, students will be able to utilize AI simulation to propose "three-win decision-making schemes" with financial precision and policy persuasiveness for urban sustainable development.
Target Audience
The course welcomes cross-disciplinary students and does not require a programming background.
Course Details
- Selection Date: March 9, 2026
- Course Period: March 13, 2026, to April 24, 2026
- Total Hours: 16 hours
- Class Time: Fridays, 13:20-15:10 (first two classes), 13:20-16:20 (subsequent classes)
- Location: Online
- Enrollment Limit: 15 students (open to external students, with priority given to students from National Yang Ming Chiao Tung University)
- Prerequisites: Basic Excel operation concepts or related knowledge and skills
Course Materials
- Cheng, J.-H. (2025). Pedaling towards net zero: AI, policy, and incentives drive a cycling revolution. Transportation Research Interdisciplinary Perspectives, 34.
- Book: "Power BI Most Powerful Entry: AI Visual Chart + Intelligent Decision + Cloud Sharing" (Second Edition) by Hong Jin-Kui.
Assessment
- Attendance and Participation: 30%
- Regular Assignments: 30%
- Final Outcome: 40%
Course Outline
The course is structured into six units, each focusing on a different aspect of integrating AI, data analysis, and policy design for urban sustainability. These include:
- Unit 1: Theory Construction - Safety, Health, and Avoidance Costs
- Unit 2: AI Data Practice I - Seeing the Value of Electricity
- Unit 3: AI Data Practice II - Health and Reward Model
- Unit 4: AI Data Practice III - Dashboard Visualization
- Unit 5: Policy Simulation - Reward Scheme Design
- Unit 6: Outcome Presentation - Simulated City Council Proposal
Frequently Asked Questions
Answers to common questions about the course, including how to enroll, the policy on dropping the course, and what to expect in terms of assessment and outcomes, are provided.