APP CHM C202
Data Management in Science
Grades
3.73
Average grade awarded in APP CHM C202. Not a student rating: this is what the grades were.
In the A range
85%
of the 33 letter grades
D, F or W
0.0%
of every letter grade awarded, plus withdrawals
Taken pass/no pass
-
the registrar has this letter grade only this term
The registrar's own records: 33 grades over 1 term, Fall 2021 to Fall 2025. Every instructor is pooled here.
What is inside that record
No summer session is in that record.
The table below splits them.
Historical grades for all professors, across recorded terms. The course summary above includes all professors.
- A 10 · 30.3%
- A- 18 · 54.5%
- B+ 5 · 15.2%
Percentages are of the 33 letter grades. Grey bars are non-letter outcomes.
How the non-letter outcomes are counted
They are excluded from the GPA entirely rather than scored, because counting a P as a 4.0 would be a fabrication.
By instructor
| Instructor | Predicted GPA | Raw | n | Terms | A range | Workload | Spring 2026 |
|---|---|---|---|---|---|---|---|
| LIU, CHONG reviews ↗ | 3.74 | 3.73 | 33 | 1 | 85% | - | not teaching it |
Why Predicted is not the Raw average
“Predicted” is shrunk toward the course average, which is itself shrunk toward the department, so an instructor with a handful of students sits near the course mean rather than topping the list.
Grade records describe outcomes. For what a course is like to take, read student reviews written on dibs below or follow the separate external review link.
Workload and assignments
Work types reported in BruinWalk reviews of this course, across recorded instructors and terms. They may differ from this term's syllabus.
dibs has not read this course’s reviews, so it cannot say what kind of work it sets. That is dibs not having looked. It is not a course without papers or exams, and the reviews linked below are the answer until dibs catches up.
From the registrar's catalog
(Formerly numbered 202.) Lecture, four hours. Recommended preparation: general coding experience in Python 3. Trains students for different aspects of data management in science. Topics include introduction and application of statistical tests, using Python to help sort data, and brief explanation of machine learning and its role in data analysis. With real-life examples and interactive in-class discussions, students are equipped with necessary data-management skills in both academic and industrial settings. Concurrently scheduled with course C102. Letter grading.
Sections in Spring 2026
From the people who took it
Student reviews
What taking APP CHM C202 was like: the work, the teaching, and what students wish they’d known.
Your experience could be the first.
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