DATA606

Algorithms for Data Science

Prerequisite: DATA602. Restriction: Must be in the Data Science Post-Baccalaureate Certificate of Professional Studies or Master of Professional Studies in Data Science and Analytics program. Credit only granted for: DATA606 or CMSC644. Formerly: CMSC644. Provides an in-depth understanding of some of the key data structures and algorithms essential for advanced data science. Topics include random sampling, graph algorithms, network science, data streams, and optimization.

Spring 2026

1 review
Average rating: 4.00

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Spring 2025

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Average rating: 4.00

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Past Semesters

1 review
Average rating: 4.00

1 review
Average rating: 4.00

1 review
Average rating: 4.00

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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 3.71 between 352 students*

DATA606 Grade Distribution+-0510152025303540455055606570758085% of studentsABCDFWother
A-: 6.82%
A: 48.58%
A+: 28.98%
B-: 0.57%
B: 4.55%
B+: 4.26%
C-: 0.85%
C: 0.28%
C+: 1.7%
D-: 0.28%
D+: 0.28%
F: 1.7%
W: 1.14%
* "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.