A Paradigm Shift in Teaching Machine Learning to Sustainable City Management Master Students

Teaching machine learning (ML) to students with diverse backgrounds, such as those in the Master in Sustainable City Management program, presents unique challenges.Traditional programmingbased approaches can be daunting for students unfamiliar with coding.Initially, software tools like RapidMiner, Weka, and Orange Data Mining were employed to simplify the learning process.However, this method often fell short in conveying deep ML concepts, which often resulted in a superficial understanding.With the advent of user-friendly coding aids like ChatGPT, a transition to Python-based instruction was implemented.Additionally, the incorporation of active learning strategies has further enhanced student engagement and understanding.This shift has shown to improve comprehension and practical skills, evidenced by higher median and maximum grades on the evaluation tool, a final project.A multiple linear regression analysis suggested that performance in "Big Data" significantly predicts grades on the Artificial Intelligence module, and the teaching approach has a marginally significant impact.Subjective analysis by the professor, also proved a better grasp of the concepts by the students.