DAMG 6105 — Data Science Engineering with Python

4 semester hoursGraduateLectureusually offered: fall, springtypical days: TBostonOnlineSeattle, WASilicon Valley, CAOnlineTraditional

Studies the Python programming language with data science as the application domain. Offers students an opportunity to learn how to perform complex numerical calculations, fixed data types, space efficiency, and vector manipulations. Covers tools and techniques for manipulating tables, spreadsheets, and group and pivot tables involving extremely large data sets. Covers large multidimensional arrays and matrices and the high-level mathematical functions to operate on these arrays. Studies how to use Python to manipulate the classic math and science algorithms. Analyzes helper functions such as linear and nonlinear regression, integration, Fourier transformations, numerical optimization, etc. Includes higher-level classes for manipulating and visualizing data. Applies tools and techniques to classical data science using cases such as time series forecasting, social network analysis, text analytics, and big data processing.

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Fall 202335313140%26.0
Spring 202433610036%21.3
Fall 202436912655%19.0
Spring 20251203067%10.0
Fall 202534411040%22.0
Spring 20262386658%14.0

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 18% · T 72% · W 11% · Th 0% · F 42%

Common patterns: TF (42% of sections), T (30% of sections), M (18% of sections), W (11% 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

CSYE 6305, CSYE 7105, CSYE 7380, DAMG 7105, DAMG 7245, DAMG 7250, DAMG 7325

Courses that list DAMG 6105 in their prerequisites.

Links

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