CS 207 - Introduction to Data Science

Credits: 4

This course will provide a broad overview of data science’s different areas, from statistics, machine learning to data engineering and many data science applications. The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. This course is designed to provide a non-technical introduction to the data science approach. It is intended both for students from non-quantitative fields and those from a quantitative field who are interested in data science. The pre-requisite for this course includes working knowledge in high school math (Math 108 or equivalent), a course in introductory statistics (at the level of Math 147, Math 148 or AP statistics with grade 3+, or equivalent). It is recommended that a student have some understanding of scientific research. Prior programming experience is NOT required. Software: it is expected that both R and python programming will be introduced in this course. CS majors may only use this as free-elective credit. Does not provide any prerequisites for courses in the CS major or minor. Term offered varies.