STATS 21
Python and Other Technologies for Data Science
Grades
3.85
Average grade awarded in STATS 21. Not a student rating: this is what the grades were.
In the A range
88%
of the 650 letter grades
D, F or W
0.6%
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: 650 grades over 9 terms, 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, and term averages across those 9 terms ran 3.69 to 4.00.
Historical grades for all professors, across recorded terms. The course summary above includes all professors.
- A+ 84 · 12.9%
- A 437 · 67.2%
- A- 54 · 8.3%
- B+ 32 · 4.9%
- B 28 · 4.3%
- B- 5 · 0.8%
- C+ 1 · 0.2%
- C 4 · 0.6%
- C- 1 · 0.2%
- D 1 · 0.2%
- F 3 · 0.5%
- P 2 of 655
- I 3 of 655
Percentages are of the 650 letter grades. Grey bars are non-letter outcomes: passes (P) and incompletes (I).
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 | Summer Session C 2026 |
|---|---|---|---|---|---|---|---|
| CHEN, MILES SATORI reviews ↗ | 3.79 | 3.79 | 415 | 6 | 84% | very light | not teaching it |
| LEW, VIVIAN reviews ↗ | 3.94 | 3.95 | 235 | 3 | 96% | - | 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.
What comes first
The chain dibs can see is 5 courses long before STATS 21. Read from Fall 2026, because dibs has not read a class page for STATS 21 in Summer Session C 2026 and a department can change what it requires. This is a floor, not a deadline: dibs has not read a class page for STATS 12, so the real chain can only be longer than this, never shorter.
Counted in courses rather than quarters: dibs does not know which of them a department lets you take together.
From the registrar's catalog
Lecture, three hours; discussion, one hour. Enforced requisite: course 20. Covers use of Python and other technologies for data analysis and data science. Focus on programming with Python and selection of its libraries: NumPy, pandas, matplotlib, and scikit-learn, for purpose of data processing, data cleaning, data analysis, and machine learning. Other technologies covered include Jupyter notebook and Git. Intended for Data Theory majors as introduction to Python language and libraries most frequently used in data science. Letter grading.
Sections in Summer Session C 2026
From the people who took it
Student reviews
What taking STATS 21 was like: the work, the teaching, and what students wish they’d known.
Your experience could be the first.
No student reviews are available to read on dibs for this course yet. Took it? Tell the next person what helped, what was hard, and how you spent your time.
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External reviews are separate and do not count toward the dibs rating.