I took 17 credits this semester. My GPA was 3.98.

Course NameTeacher老師CreditsScore
Introduction to Analysis (II), Honor ClassWANG Kuo-Zhong王國仲4B+
SoftballHUANG Shan-Ying黃杉楹0A
ManagementHSIAO Chan蕭嬋3A+
StatisticsWANG Hsiuying王秀瑛3A
Computational MathematicsWU Chin-Tien吳金典3A+
Introduction to Data Science: Concepts & PracticeCHEN Chang-Sheng陳昌盛2A+
Data and Everyday LifePERNG Sung-Yueh彭松嶽2A

Seventeen credits, and still a heavy load.

Introduction to Analysis (II), Honor Class

The same denser sophomore section as the first semester (still no honors credit attached), with the same clear notes and the same heavy, Baby-Rudin-grade homework. The TA’s support made a real difference this time, and I edged the grade up to a B+.

Computational Mathematics

The real value here is in the homework — problem sets that actually let you practice, the kind that feel good once you finally work them out. You can skip the lectures, but you have to do that homework. Grading is generous, with a cheat sheet allowed in exams.

Statistics

A gently paced, conventionally taught course that I took mainly for scheduling reasons. Graded on just a midterm and a final, with no attendance or homework, and the exams come straight from the assigned problems — easy enough once you study them.

Management

Lively classes and super sweet — the exams are common-sense multiple choice. Graded on exams, a report, and participation.

Data and Everyday Life

About how data is gathered in society. Graded on reports, a project, and participation, with the occasional roll call; the marking was less generous than I expected.

Introduction to Data Science: Concepts & Practice

A general-education course, and a manageable one: do the homework and the exams and full marks are within reach. Excel formulas are the crux. Super chill, no roll call, open-book (and open-internet) exams, plus homework and a project.

Softball

Attendance is 40% — full attendance passes.