Section outline

  • Introduction to Data Science with R

    Data science is the process of answering questions with data. This course provides a broad introduction to the principles and practice of modern data science using the statistical programming language R. Students will learn to acquire, clean, transform, explore, visualize, and model data to answer meaningful questions and communicate evidence-based conclusions. Emphasis is placed on developing computational thinking, data literacy, effective data communication, and reproducible analytical workflows. No prior experience with data science, statistics, or programming is required.

    Instructor: Anjali Thapar (BYC 212, x5008, athapar@brynmawr.edu)
    Class Meetings: Park 336, Tuesdays and Thursdays 2:40-4:00 pm 

    Prof. Anjali's Office Hours: Wednesdays 11:30 am to 1 pm and by appointment.

    TA Drop-IN Session Hours:

    • Fridays from 4:00 to 5:00 pm (Zoom Only)
    • Sundays from 3:00 to 5:00 pm (Bettws-y-Coed, Room 127, In-Person and Zoom)
    • Mondays from 7:00 to 9:00 pm (Bettws-y-Coed, Room 127, In-Person and Zoom from 7-8 pm)

    Zoom link for all TA Drop-In Sessions: https://brynmawr-edu.zoom.us/j/99320486778

    Required Readings: We will primarily be using free online resources for this course. The links to the resources will be posted to the course Moodle page.

    The following textbook is a free online supplemental resource: 

    Wickham, H., Cetinkaya-Rundel, M., & Grolemund, G. (2023). R for Data Science (2e). Available at https://r4ds.hadley.nz/.

    NOTE: Students will need to bring a laptop to class. Students who do not have a personal laptop can check out laptops from Canaday Library and/or contact the instructor.