2015 CS109A: Harvard's Data Science
Learning from data in order to gain useful predictions and insights. This third iteration of the course continues on the same ideas as the previous two; use methods of the five key facets of an investigation: data wrangling, cleaning, and sampling to get a suitable data set; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization, stories, and interpretable summaries.
Python was used for all programming assignments and projects. All lectures are posted here.
Instructors
Python was used for all programming assignments and projects. All lectures are posted here.
Instructors
- Joe Blitzstein, Statistics
- Hanspeter Pfister, Computer Science
- Verena Kaynig-Fittkau, Computer Science
- Rahul Dave, Head TF