EECS 448·Electrical Engineering & Computer Science·3 credits·400 — Advanced undergradEstimated metrics
Applied Machine Learning for Modeling Human Behavior
Estimated data.The metrics below are derived from this course's level and subject, not from verified student outcomes. Treat them as a starting point, not a promise.
Workload
17
hrs / week
≈ EECS avg
Difficulty
5/5
Very hard
above EECS avg (4.7)
Median grade
B+
mean 3.4 GPA
≈ EECS avg
% earning A
43%
A+, A, or A−
Grade distribution
Median B+ · Mean 3.40 GPA · Estimated
3%
18%
22%
23%
18%
9%
4%
2%
1%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
E
Similar courses in this subject
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Resources for EECS students
How to read these numbers
- Workload — total hours/week including lecture, assignments, and exam prep.
- Difficulty (1–5) — conceptual rigor and pace, not just hours.
- Median grade — the middle student's final letter; mean GPAaverages everyone's grade points.
- % earning A — share of students finishing with A+, A, or A−.
- Comparisons are against this subject's average, so you can tell whether a number is high for the discipline.