Teaching

Instructor

IDSC 4444: Descriptive and Predictive Analytics (Fall 2024)

🏆 Recipient of the Ph.D. Student Teaching Award
Course Description:
This course exposes students to data mining and machine learning methods, including exploratory methods (e.g., association rules and cluster analysis), predictive methods (e.g., K-NN and decision trees), and text mining methods. It introduces fundamental concepts in Business Analytics and Machine Learning, teaching students what these methods can and cannot do, how to select the right method for a given problem, and providing hands-on experience with R Programming.
Course Evaluation:
5.67 out of 6 (31 students, 93.55% response rate)
Selected Student Reviews:
  • "She actively asked for feedback from students and then applied it. For example, we asked for her to post completed lab demos before class, rather than waiting until after class, so that we could follow along with them and use them if we were confused. She was open to this feedback and started doing it, greatly helping us follow along in class."
  • "Doing an exit ticket and then reviewing concepts that weren't completely clear from the previous lecture at the beginning of the next lecture has been super helpful. I also think prof. Yoon's pace has been perfect throughout the entirety of the class."
  • "Sojung always reviewed information of previous lecture before we learned new material which was super helpful. She also answered my questions really well in office hours. She helped me most with my learning by providing accommodations when necessary and always treated me with respect."

Teaching Assistant

LevelCourseTerms
GraduateIDSC 6444 and IDSC 6446 Business Analytics for Managers I and II2024, 2025
GraduateMABA 6341 Data Visualization2025
GraduateMSBA 6431 Advanced Topics in Business Analytics2023
GraduateMSBA 6040 Information Technology Management2021
UndergraduateIDSC 4110 Data Engineering for Business Analytics2022, 2024
UndergraduateIDSC 4444 Descriptive and Predictive Analytics2021, 2024