Pavlos Protopapas & Natesh Pillai
COMPSCI 1090A | Fall 2024 | Course Listing | Canvas Site
Monday, Wednesday and Friday, 9:00 AM – 10:15 AM
Data Science 1 is the first half of a one-year introduction to data science. The course will focus on the analysis of messy, real life data to perform predictions using statistical and machine learning methods. Material covered will integrate the five key facets of an investigation using data: (1) data collection – data wrangling, cleaning, and sampling to get a suitable data set; (2) data management – accessing data quickly and reliably; (3) exploratory data analysis – generating hypotheses and building intuition; (4) prediction or statistical learning; and (5) communication – summarizing results through visualization, stories, and interpretable summaries. Part one of a two part series. The curriculum for this course builds throughout the academic year. Students are strongly encouraged to enroll in both the fall and spring course within the same academic year.
Recommended Prep: Programming knowledge at the level of CS 50 or above, and statistics knowledge at the level of Stat 100 or above (Stat 110 recommended).