Covers fundamentals of data management and analysis for industrial engineers, including database strategies, preprocessing, visualization, and modeling using MySQL and R.
Students found Tina Xu’s lectures boring and repetitive, often describing them as monotone slide readings. While several reviewers noted that homework was similar to in-class problems and that attendance earned extra credit, opinions on exam difficulty varied; some found them manageable, while others described them as decently hard with low preparation guidance.
Fundamentals of Industrial Data Analytics covers using data analytics for data-driven decisions, emphasizing application to industrial engineering problems via modeling strategies.
Tina Xu offered a 3% extra credit and weekly homework in ISYE 412, with students describing the course as an easy A if you attended lectures and studied. She provided example problems in every lecture and gave clear grading, though some found the lectures dull.