DATA602

Principles of Data Science

Restriction: Must be in one of the following programs: (Data Science Post-Baccalaureate Certificate, Master of Professional Studies in Data Science and Analytics, or Master of Professional Studies in Machine Learning). Cross-listed with: MSML602. Credit only granted for: DATA602, MSML602 or CMSC641. Formerly: CMSC641. An introduction to the data science pipeline, i.e., the end-to-end process of going from unstructured, messy data to knowledge and actionable insights. Provides a broad overview of what data science means and systems and tools commonly used for data science, and illustrates the principles of data science through several case studies.

Spring 2026

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Fall 2025

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1 review
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Spring 2025

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Past Semesters

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3 reviews
Average rating: 5.00

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Average rating: 2.00

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2 reviews
Average rating: 3.50

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 3.32 between 801 students*

DATA602 Grade Distribution+-051015202530354045505560657075% of studentsABCDFWother
A-: 16.85%
A: 30.09%
A+: 27.22%
B-: 0.87%
B: 3%
B+: 7.87%
C: 0.62%
C+: 0.75%
D: 0.12%
F: 0.37%
W: 12.23%
* "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.