STA 199: Intro to Data Science
Intro to data science and statistical thinking. Learn to explore, visualize,and analyze data to understand natural phenomena, investigate patterns, model outcomes,and make predictions, and do so in a reproducible and shareable manner. Gain experience in data wrangling and munging, exploratory data analysis, predictive modeling, data visualization, and effectively communicating results. Work on problems and case studies inspired by and based on real-world questions and data. The course will focus on the R statistical computing language.
Course info
Lecture | All Students | Wednesday and Friday 10:15 - 11:30am |
Labs | Lab 7 | Tuesday 1:45 - 3:00pm |
Lab 8 | Tuesday 3:30 - 4:45pm | |
Lab 9 | Tuesday 5:15 - 6:30pm |
Click on the schedule tab to keep up with all activities and assignments.
Teaching team and office hours
Click here for an updated spreadsheet of office hours with locations and links.
Instructor | Prof. Alexander Fisher | Mon, Thu 4-5p |
TAs | Steven Winter | Fri 9-11a |
Camilla Yu | Tue 4-6p | |
Rob Kravec | Mon 5-7p | |
Mariana Izon | Tue 6-8p | |
Shannon Houser | Mon, Wed 12-1p | |
Evan Dragich | Thu 10-12p | |
Margaret Reed | Wed 2-4p | |
Shirley Mathur | Thu, Fri 6-7p |