Course Descriptions

The Course Descriptions catalog describes all undergraduate and graduate courses offered by Michigan State University. The searches below only return course versions Fall 2000 and forward. Please refer to the Archived Course Descriptions for additional information.

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CMSE 495  Experiential Learning in Data Science (W)

Semester:
Fall of every year, Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 2   Lab Hours: 4
Prerequisite:
(CSE 232 and CMSE 382) and completion of Tier I writing requirement
Restrictions:
Open to seniors.
Description:
Team-based data science projects on realistic, large-scale data.
Effective Dates:
FS19 - FS22


CMSE 495  Experiential Learning in Data Science (W)

Semester:
Fall of every year, Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 2   Lab Hours: 4
Prerequisite:
(CSE 232 and CMSE 382) and completion of Tier I writing requirement
Restrictions:
Open to seniors.
Description:
Team-based data science projects working with real-world data in collaboration with client/company sponsors. Practice in software development, data collection, curation, modeling, scientific visualization and presentation of results. Students may be required to sign a non-disclosure agreement (“NDA”) or an assignment of intellectual property rights (“IP Assignment”) to work with some project sponsors.
Effective Dates:
SS23 - Open