2022

2022

  • [Undergraduate] ISM 218: Database Systems (Spring, UNCG, USA)
    • Face-to-Face Section: Enrollment 38; Evaluation 4.4/5.0
    • Online Section: Enrollment 57; Evaluation 4.51/5.0

2021

  • [Graduate] ISM 645: Principles of Predictive Analytics (Fall, UNCG, USA)
    • Face-to-Face Section: Enrollment 23; Evaluation 4.43/5.0
    • Online Section: Enrollment 73; Evaluation 4.56/5.0
  • [Undergraduate] ISM 218: Database Systems (Spring, UNCG, USA)
    • Face-to-Face (Hybrid) Section: Enrollment 40; Evaluation 4.36/5.0
    • Online Section: Enrollment 39; Evaluation 4.05/5.0

2020

  • [Graduate] ISM 645: Principles of Predictive Analytics (Fall, UNCG, USA)
    • Face-to-Face Section: Enrollment 21; Evaluation 4.43/5.0
    • Online Section: Enrollment 80; Evaluation 4.54/5.0
  • [Undergraduate] ISM 218: Database Systems (Spring, UNCG, USA)
    • Face-to-Face (Hybrid) Section: Enrollment 40; Evaluation 4.44/5.0
    • Online Section: Enrollment 58; Evaluation 3.60/5.0

2019

  • [Graduate] ISM 645: Principles of Predictive Analytics (Fall, UNCG, USA)
    • Face-to-Face Section: Enrollment 53; Evaluation 4.42/5.0
    • Online Section: Enrollment 54; Evaluation 3.97/5.0
  • [Undergraduate] MGT0044: Decision Support Systems (Spring, Hansung University, Korea)
    • Enrollment 28; Evaluation 4.76/5.0

Research Methodology Seminars

  • Korea Causal Inference Summer Session 2021 (Summer 2021, Online)
    • Online sessions for introducing research methodologies and data analytical approaches in pursuit of causal inference
    • Module 1: Research Design for Causal Inference (10 Sessions)
    • Module 2: Machine Learning for Causal Inference (8 Sessions)
    • Session website
  • Social Science of COVID-19: From the Perspective of Causal Inference (Summer 2020, Online)
    • Online sessions to review empirical studies on COVID-19 with a particular focus on causal inference
    • Session website
  • MIS Summer Session 2019 - Experimental Empirical Methods (Summer 2019, KAIST)
  • MIS Summer Session 2018 - Research Design for Data Analytics (Summer 2018, KAIST)
    • Non-credit session for PhD/MS students
    • Module 1: (lecture) Research Design for Data Analytics
    • Module 2: (hands-on) Causal Inference with STATA
    • Module 3: (hands-on) Deep Learning with PyTorch
    • Session website / GitHub for hands-on codes
  • MIS Summer Session 2017 - Introduction to Economics of IS and Research Methodology (Summer 2017, KAIST)