UC_BERKELEY · DATASCI · COURSE SHEET
DATASCI 2553 creditsSee offeringsHas prerequisites
Machine Learning Systems Engineering
CT Score
1500
#0 of 0 in DATASCI
Difficulty
—/10
Workload
—h/wk
Median grade
A
from grade distribution
Would take again
—
n = 0 verified
ESTIMATEStarted from public course data. The first verified student reviews replace these numbers.
Grade distribution
Student-reported · course feedback surveys30.1%
62.4%
2.9%
1.2%
0.5%
0.5%
0.2%
2.2%
A+
A
A-
B+
B
B-
C
F
By professor: same course, different game
PROFESSORSCOREGRADEHRS/WKTERMS
Professor ratings →Sections
No section data for this term yet.
In the tree
DATASCI 205 and DATASCI 207 AND MIDS students only. We assume you are familiar with generating predictions from a trained machine learning model. Familiarity with command line (Bash), Python, and Git. We assume you have a working knowledge of SSH, Ports, and familiarity with networking concepts such as DNS.→DATASCI 255→unlocks 0 courses
No mapped courses require this one yet. See on the map →
Study groups
0 active🔒 Verified-only writes. You post as “sophomore, lecture section”: real enough to trust, anonymous enough to be honest.