Undergraduate Seminar
Data-centered research exercises
This section describes the undergraduate seminar. Unlike graduate school, where students aim to complete a thesis, students in their second through fourth years gradually build the ability to work with data, formulate questions, present, and think critically.
Second year: opening the door to practice
Second-year students meet for two consecutive class periods, combining presentation exercises with hands-on work in VS Code.
The focus is on viewing, organizing, and explaining data—developing presentation skills, habits of documenting their work, and making analysis visible to others.
Through GitHub Education and Copilot for students, I aim to give students experience with collaborative work using generative AI and managing outputs.
Third year: preparing for research and external connection
Third-year students prepare to join data science competitions and joint seminars with other universities.
The emphasis is not only on analytical methods but on explaining ideas to others, engaging with questions, and presenting as a team—experience closer to research practice.
The goal is to learn how to handle data and structure presentations in a research setting, preparing for further research activity.
Fourth year: bringing research together for the graduation thesis
The aim is not merely to “be able to analyze” but to formulate research questions, draw insights from data, and communicate them to others.
In the fourth year—the capstone of the undergraduate seminar—students focus on writing the graduation thesis while developing research thinking and presentation skills.
In practice, thesis writing often intensifies after the job-search period; the seminar therefore also cultivates the ability to communicate research in settings beyond the university.