CS 307

Spring 2025 All Classes

All Classes

Modeling and Learning in Data Science

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Credit: 4 hours.

Introduction to the use of classical approaches in data modeling and machine learning in the context of solving data-centric problems. A broad coverage of fundamental models is presented, including linear models, unsupervised learning, supervised learning, and deep learning. A significant emphasis is placed on the application of the models in Python and the interpretability of the results.

Prerequisite: STAT 207; one of MATH 225, MATH 227, MATH 257, MATH 415, MATH 416, ASRM 406.

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CS 307 class schedule data for spring 2025
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	71618	Discussion/ Recitation Lecture	AL1 AL1	9:30AM -10:45AM 9:30AM -10:45AM	F MW	2100 Sidney Lu Mech Engr Bldg 2100 Sidney Lu Mech Engr Bldg	Dalpiaz, D Dalpiaz, D	Part of Term: 1 Date Range: 01/21/25-05/07/25 Restriction(s): Restricted to Undergrad - Urbana-Champaign. Restricted to Business Undeclared or Information Sciences + DS or Astronomy + Data Science or Finance + Data Science or Accountancy + Data Science or Business + Data Science major(s). Not intended for CS and blended CS majors students.
	73190	Discussion/ Recitation Lecture	AL2 AL2	9:30AM -10:45AM 9:30AM -10:45AM	F MW	2100 Sidney Lu Mech Engr Bldg 2100 Sidney Lu Mech Engr Bldg	Dalpiaz, D Dalpiaz, D	Part of Term: 1 Date Range: 01/21/25-05/07/25 Restriction(s): Restricted to Undergrad - Urbana-Champaign. Not intended for Finance + Data Science or Information Sciences + DS or Astronomy + Data Science or Accountancy + Data Science or Business + Data Science major(s). Not intended for First Time Freshman students.