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Winter 2024

 

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Data Science (DSCI)
204 Pacific Hall,
College of Arts & Sciences
8 - No cost for class textbook materials.
Q - Tentative
Course Data
  DSCI 102   Foundat Data Science 2 4.00 cr.
This course expands upon critical concepts and skills introduced in DSCI 101. Topics include the normal distribution, confidence intervals, regression, and classifiers. Sequence with DSCI 101.
Grading Options: Optional; see degree guide or catalog for degree requirements
Instructor: Muehleisen AE-mail


Instructor: Sventek JE-mail Office:   333 Deschutes Hall
Phone:   (541) 346-3473
See CRN for CommentsPrereqs/Comments: Prereq: DSCI 101, MATH 101 (or equivalent placement score) or any other college-level math course.
Course Materials
 
  CRN Avail Max Time Day Location Instructor Notes

Lecture

21691 22 75 1400-1520 tr 229 MCK Muehleisen A !8
Sventek J

Final Exam:

1230-1430 m 3/18 229 MCK
 
Associated Sections

+ Lab

21692 15 25 0900-0950 f 203 CON Dragu J  

+ Lab

21693 7 25 1200-1250 f 253 STB Muehleisen A Q

+ Lab

21694 0 25 1100-1150 f 185 LIL Dragu J  
Academic Deadlines
Deadline     Last day to:
January 7:   Process a complete drop (100% refund, no W recorded)
January 13:   Drop this course (100% refund, no W recorded; after this date, W's are recorded)
January 13:   Process a complete drop (90% refund, no W recorded; after this date, W's are recorded)
January 14:   Process a complete withdrawal (90% refund, W recorded)
January 14:   Withdraw from this course (100% refund, W recorded)
January 15:   Add this course
January 15:   Last day to change to or from audit
January 21:   Process a complete withdrawal (75% refund, W recorded)
January 21:   Withdraw from this course (75% refund, W recorded)
January 28:   Process a complete withdrawal (50% refund, W recorded)
January 28:   Withdraw from this course (50% refund, W recorded)
February 4:   Process a complete withdrawal (25% refund, W recorded)
February 4:   Withdraw from this course (25% refund, W recorded)
February 25:   Withdraw from this course (0% refund, W recorded)
February 25:   Change grading option for this course
Caution You can't drop your last class using the "Add/Drop" menu in DuckWeb. Go to the “Completely Withdraw from Term/University” link to begin the complete withdrawal process. If you need assistance with a complete drop or a complete withdrawal, please contact the Office of Academic Advising, 101 Oregon Hall, 541-346-3211 (8 a.m. to 5 p.m., Monday through Friday). If you are attempting to completely withdraw after business hours, and have difficulty, please contact the Office of Academic Advising the next business day.

Expanded Course Description
This course prepares students to apply computational, statistical, and inferential techniques to large data sets. Students will learn to obtain data from public sources, distill critical information, characterize the data using statistical techniques, and make quantitative predictions based on their analyses. Topics include the normal distribution, confidence intervals, regression, and classifiers. Ethical concerns resulting from use of the techniques in this course will be addressed.
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Release: 8.11