DS 5020 — Introduction to Linear Algebra and Probability for Data Science

4 semester hoursGraduateLectureusually offered: fall, springtypical days: M/WBostonPortland, MaineSilicon Valley, CALive CastTraditional

Offers an introductory course on the basics of statistics, probability, and linear algebra. Covers random variables, frequency distributions, measures of central tendency, measures of dispersion, moments of a distribution, discrete and continuous probability distributions, chain rule, Bayes’ rule, correlation theory, basic sampling, matrix operations, trace of a matrix, norms, linear independence and ranks, inverse of a matrix, orthogonal matrices, range and null-space of a matrix, the determinant of a matrix, positive semidefinite matrices, eigenvalues, and eigenvectors.

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Fall 202331210012%29.3
Spring 20243289729%23.0
Fall 2024122010%18.0
Spring 202533111128%26.7
Fall 202522315815%67.5
Spring 202638211472%10.7

Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.

Meeting times

Share of recent sections by weekday: M 69% · T 25% · W 52% · Th 15% · F 16%

Common patterns: MW (52% of sections), TF (16% of sections), T (9% of sections), MR (9% of sections), M (8% of sections), R (6% of sections) — in patterns, R means Thursday

Professors

Fall

Spring

Percentages are each professor's average share of the season's enrolled students in recent terms.

Unlocks

DADS 7275, EECE 5612

Courses that list DS 5020 in their prerequisites.

Links

Official catalog (DS course descriptions) · Student reviews on RateMyHusky · All DS courses · Plan it at numap.app