Data science is the study of extracting value from data. This course will introduce students to the methods and tools used in data science to obtain insights from data. Students will learn how to analyze data arising from real-world phenomena while mastering critical concepts and skills in computer programming and statistical inference. The course will involve hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. This class is ideal for students looking to increase their digital literacy and expand their use and understanding of computation and data analysis across disciplines. No prior programming or math background is required.
- Course number
- BC COMS 1016 - students from all majors are welcome!
- Instructor
- Adam Poliak
- Teaching Assistants
- Course Staff
- Website
- https://coms1016.barnard.edu/
- Discussion Forum
- EdStem
- Time and place
- Spring 2022, TR 11:40am-12:55pm, Location: Dianna 504
- Lab 01 W: 12:00-2:00pm
- Lab 02 R: 4:00-6:00pm
- Lab 03 F: 9:00-11:00am
- Office Hours
- Times
- Prerequisites
- None - no prior programming or college-math background is required
- Modes of Thinking Requirement
- Thinking Quantitatively and Empirically
- Thinking Technologically and Digitally
- Course Readings
- Each lecture has an accompanying chapter/section of the textbook
- Some lectures will have accompanying optional reading related to the lecture’s topic
Grading
- Homeworks: 25%
- Labs: 10%
- Projects: 20%
- Midterm: 15%
- Final Project: 25%
- Participation: 5%
- Late day policy
- To account for issues that arise in these uncertain times, each student has 10 late days for the homeworks and projects.
See the Policies for more details.
Acknowledgments
A Google Cloud Education grant is supporting the computational infrastructure for the course.
Eric Van Dusen, his staff, and The Data Science Education Community have been very helpful
in adopting this course at Barnard.