This course utilizes a quantitative approach to explore fundamental concepts in data science. Students will develop key skills in programming and statistical inference as they interact with real-world data sets across a variety of domains. Ethical and privacy concerns are explored. Sequence with DSCI 102.
Grading Options:
Optional; see degree guide or catalog for degree requirements
Process a complete drop (100% refund, no W recorded)
April 5:
Drop this course (100% refund, no W recorded; after this date, W's are recorded)
April 5:
Process a complete drop (90% refund, no W recorded; after this date, W's are recorded)
April 6:
Process a complete withdrawal (90% refund, W recorded)
April 6:
Withdraw from this course (100% refund, W recorded)
April 7:
Add this course
April 7:
Last day to change to or from audit
April 13:
Process a complete withdrawal (75% refund, W recorded)
April 13:
Withdraw from this course (75% refund, W recorded)
April 20:
Process a complete withdrawal (50% refund, W recorded)
April 20:
Withdraw from this course (50% refund, W recorded)
April 27:
Process a complete withdrawal (25% refund, W recorded)
April 27:
Withdraw from this course (25% refund, W recorded)
May 18:
Withdraw from this course (0% refund, W recorded)
May 18:
Change grading option for this course
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 utilizes a quantitative approach to explore fundamental concepts in data science. Students will develop key skills in programming and statistical inference as they interact with real-world data sets across a variety of domains. Ethical ramifications of data collection, data-driven decision making, and privacy will be explored. This course is intended to be accessible to students without prior experience in computer programming or statistics.
