Course description Introduction to Data Science provides a practical introduction to the burgeoning field of data science. The course introduces students to the essential tools for conducting data-driven research, including the fundamentals of programming techniques and the essentials of statistics. Students will work with real-world datasets from various domains; write computer code to manipulate, explore, and analyze data; use basic techniques from statistics and machine learning to analyze data; learn to draw conclusions using sound statistical reasoning; and produce scientific reports. No prior knowledge of programming or statistics is required.
Every student has a total of 6 grace days they can use throughout the term (except for Project 3) to avoid a lateness penalty of 10% per 24 hours, rounded up to the nearest whole number of days. You cannot use more than three grace days at a time.
The morning section meets at McComick Hall 101 on Zoom on Tues 11:00am-12:20pm and Thurs 11:00am-12:20pm Eastern Time.
The afternoon section meets at Robertson Hall 001 on Zoom on Tues 3:00pm-4:20pm and Thurs 3:00pm-4:20pm Eastern Time.
See here for precept logistics/assignments and here for links.
Design credit: CS229, Jan 2019.