UC_BERKELEY · COMPSCI · COURSE SHEET
COMPSCI 1894 creditsSee offeringsHas prerequisites
Introduction to Machine Learning
CT Score
1500
#0 of 0 in COMPSCI
Difficulty
7.6/10
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 surveys8.3%
29.9%
12.5%
11.1%
9.3%
6.9%
2.2%
2.9%
1.6%
0.2%
0.8%
0.3%
1.3%
1.7%
11.1%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F
NP
P
By professor: same course, different game
PROFESSORSCOREGRADEHRS/WKTERMS
JM
Jitendra Malik
1 community ratings
10
——JL
Jennifer Listgarten
17 community ratings
8.5
——AD
Alex Dimakis
15 community ratings
8.3
——JS
Jonathan Shewchuk
11 community ratings
9.5
——JG
Joseph Gonzalez
16 community ratings
8.4
——SS
Saeed Saremi
1 community ratings
10
——NN
Narges Norouzi
18 community ratings
9.2
——Sections
No section data for this term yet.
In the tree
MATH 53 and MATH 54; and COMPSCI 70 or consent of instructor.→COMPSCI 189→unlocks 5 courses
5 mapped courses list COMPSCI 189 as a prerequisite. 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.