Data Engineering for Smart Cities, CCE 5502, NCKU-EE

This is a project-based course built on industry-government-academic collaboration. It combines data science theory with practical applications, focusing on real-world challenges proposed by city government departments. Throughout the semester, students work in interdisciplinary teams to solve data-driven problems using methods such as data preprocessing, exploratory analysis, predictive modeling, and result visualization. The course emphasizes teamwork, communication with non-technical stakeholders, and iterative development, aiming to equip students with both technical skills and the ability to apply them effectively in real-world urban scenarios. During this semester, we collaborated with five government departments on seven projects, including the prediction of fire and emergency response success rates, the development of a roadside parking diversion system, and the forecasting of property tax rates.

As the teaching assistant for this course, I played a key role in bridging academic learning with real-world applications through an industry-government-academic collaboration. My responsibilities was supporting team formation based on complementary strengths, and providing technical and project management guidance throughout the semester. I also facilitated communication between student teams and government partners, offered timely feedback during project presentations, and held one-on-one office hours to address students’ questions in greater depth. My contributions helped create a dynamic and supportive learning environment that encouraged hands-on learning and interdisciplinary teamwork. I was also honored to receive the Outstanding Teaching Assistant Award for my contributions to this course.