Detailed Course Information |
Fall 2026
Nov 02, 2026 |
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| CMPS 360 - Data Science Fundamentals |
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Fundamental principles, algorithms, and methods of data science. Topics include the data science lifecycle, data acquisition and representativeness, exploratory analysis, visualization, sampling, statistical inference, hypothesis testing, and causal reasoning. Core analytical techniques such as regression, classification, and predictive modeling are introduced. Data ethics, including privacy, fairness, and responsible data use, are emphasized throughout. Hands‑on projects using real‑world datasets develop practical skills in analyzing, visualizing, and communicating data‑driven insights with modern data science tools.
3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Computer Science & Engineering Department Course Attributes: Engineering Course (TUI) Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: Undergraduate level CMPS 151 Minimum Grade of D |
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