CMSC454

Algorithms for Data Science

Prerequisite: Minimum grade of C- in CMSC320, CMSC330, and CMSC351. Restriction: Permission of CMSC-Computer Science department. Credit only granted for: CMSC454 or CMSC498U. Formerly: CMSC498U. Fundamental methods for processing a high volume of data. Methods include stream processing, locally sensitive hashing, web search methods, page rank computation, network and link analysis, dynamic graph algorithms as well as methods to handle high dimensional data/dimensionality reduction.

Spring 2026

7 reviews
Average rating: 4.00

Fall 2025

7 reviews
Average rating: 4.00

Spring 2025

7 reviews
Average rating: 4.00

Past Semesters

0 reviews
Average rating: N/A

7 reviews
Average rating: 4.00

0 reviews
Average rating: N/A

7 reviews
Average rating: 4.00

7 reviews
Average rating: 4.00

0 reviews
Average rating: N/A

During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 2.95 between 259 students*

CMSC454 Grade Distribution+-051015202530354045% of studentsABCDFWother
A-: 11.2%
A: 16.99%
A+: 13.9%
B-: 12.36%
B: 11.58%
B+: 6.18%
C-: 2.32%
C: 7.72%
C+: 9.65%
D-: 0.39%
F: 0.77%
W: 6.95%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.