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Spring 2024

 

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Data Science (DSCI)
204 Pacific Hall,
College of Arts & Sciences
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: Graded for all students
Instructor: Sventek JE-mail Office:   143 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

31399 44 100 1600-1720 tr 129 MCK Sventek J !

Final Exam:

1230-1430 m 6/10 129 MCK
 
Associated Sections

+ Lab

31401 17 25 0900-0950 f 193 ANS Diaz Monzon M  

+ Lab

31402 6 25 1000-1050 f 101 PETR Diaz Monzon M  

+ Lab

31403 11 25 1200-1250 f 117 FEN Diaz Monzon M  

+ Lab

31404 10 25 1300-1350 f 193 ANS Diaz Monzon M  
Academic Deadlines
Deadline     Last day to:
March 31:   Process a complete drop (100% refund, no W recorded)
April 6:   Drop this course (100% refund, no W recorded; after this date, W's are recorded)
April 6:   Process a complete drop (90% refund, no W recorded; after this date, W's are recorded)
April 7:   Process a complete withdrawal (90% refund, W recorded)
April 7:   Withdraw from this course (100% refund, W recorded)
April 8:   Add this course
April 8:   Last day to change to or from audit
April 14:   Process a complete withdrawal (75% refund, W recorded)
April 14:   Withdraw from this course (75% refund, W recorded)
April 21:   Process a complete withdrawal (50% refund, W recorded)
April 21:   Withdraw from this course (50% refund, W recorded)
April 28:   Process a complete withdrawal (25% refund, W recorded)
April 28:   Withdraw from this course (25% refund, W recorded)
May 19:   Withdraw from this course (0% refund, W recorded)
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