Core Principles of Data Science / Fall 2023
Updates
- New Lecture is up: Machine learning - cross validataion and Next steps
Course Description
Modern technology has led to the generation of unprecedented amounts of data, prompting the need to train researchers to leverage data for decision-making in public health and medicine. This course assumes no prior R or programming knowledge and serves as a gentle, practical introduction to wrangling, visualizing, and modeling data using the R statistical programming language. We also emphasize the importance of reproducible research and effective data science communication.
Lectures
- Time: 11:30 am - 1:00 pm EST on Mondays & Wednesdays
- Location: Kresge 502
- We will be using R for all programming homework and projects.
Office Hours
Office hours will mostly be held in-person (see below). Links will be posted on Canvas if Zoom is also available.
| Day | Time | Staff | Location |
|---|---|---|---|
| Monday | 3:30 - 4:30 pm | Luke | Building 2, 4th floor, 401 (In-person only) |
| Tuesday | 2:30 - 3:30 pm | Dongdong | Zoom (link available on Canvas) |
| Wednesday | 1:00 - 2:00 pm (2-3pm on Dec 6) | Dongdong | Building 2, 4th floor, 437F (In-person only) |
| Thursday | 1:00 - 2:00 pm | Luke | Building 2, 4th floor, 401 (In-person only) |
Labs
Note that there will not be labs every week. Announcements will be posted on the course website and Canvas.
- Time: Fridays 9:45 - 11:15 am EST
- Location: Kresge LL6 (exceptions: Sep 29 - FXB G03, Oct 6 - FXB G03, Nov 3 - FXB G12)
Please note that labs will not be held during all weeks of the semester. The schedule will be posted on the course Canvas site and under Schedule.
Note that all lectures and lab sessions will be recorded and available on the course Canvas site.
Instructors
Dongdong Li
dongdongli [at] hsph.harvard.edu
Teaching Assistants
Luke Benz
lukebenz [at] g.harvard.edu