|Monday||3:00 PM - 4:00 PM (Niki)
9:00 PM - 11:00 PM (Maddie)
|Tuesday||9:00 PM - 11:00 PM (Maddie)|
|Wednesday||3:00 PM - 5:00 PM (Kaya)
5:00 PM - 7:00 PM (Niki)
9:00 PM - 11:00 PM (Maddie)
|Thursday||8:00 PM - 9:00 PM (Ryan)|
|Friday||1:00 PM - 4:00 PM (Kaya)
7:00 PM - 9:00 PM (Ryan)
|Saturday||1:00 PM - 3:00 PM (Max)|
|Sunday||6:00 PM - 9:00 PM (Sophie)|
Foundations of Data Science combines three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? 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. It also delves into social issues surrounding data analysis such as privacy and design. This course is part of Vassar's HHMI Grand Challenges on climate change.
This course does not have any prerequisites beyond high-school algebra. The curriculum and format is designed specifically for students who have not previously taken statistics or computer science courses. Students with some prior experience in either statistics or computing are welcome to enroll and will find much of interest due to the innovative nature of the course. Students who have taken several statistics or computer science courses should instead take a more advanced course.
Assistant Professor Jason Waterman
Office: SP 104.4
Office Hours: Tuesday 4:30 PM to 6:00 PM and Wednesday 1:00 PM to 3:00 PM or direct message on slack Zoom meeting link: click
Assistant Professor Monika Hu
Office: Rocky 403
Office Hours: Wednesday 10:00 AM to 12:00 PM and Thursday 11:30 AM to 12:30 PM
Zoom meeting link: click
Class: Tuesday and Thursday 1:30 pm to 2:45 pm in Sanders Classroom 212
Lab (144-51): Thursday 3:10 pm to 5:10 pm in Sanders Physics 309
Lab (144-52): Thursday 6:00 pm to 8:00 pm in Sanders Physics 309
Grades will be weighted as follows:
We would really love to see you in each and every class. We'll work on problems together during class and labs, and we will always leave time for questions. Our classes here at Vassar are small and coming to class is one of the best ways for you to learn the material.
If you know you ahead of time you will not be attending class, please let us know as soon as possible.
We hope that everyone in this class will remain happy and healthy. But, if you have a serious persistent personal issue, such as being hospitalized for an extended period or needing to leave the country for a family matter, please talk to your class advisor in the dean of studies office as soon as possible. Such issues consistently affect one’s ability to succeed in all classes, rather than just this class, and the class advisors are equipped to coordinate plans for dealing with them. We will cooperate with such plans, but we cannot construct them independently of the class advisors.
We encourage you to discuss course content with your friends and classmates as you are working on your weekly assignments. No matter what your academic background, you will definitely learn more in this class if you work with others than if you do not. Ask questions, answer questions, and share ideas liberally.
You must write your answers in your own words, and you must not share your completed work. The exception to this rule is that you can share everything related to your final project with your project partners and turn in one project for the group.
Make a serious attempt at every assignment yourself. If you get stuck, read the textbook and go over the lectures and lab discussion. After that, go ahead and discuss any remaining doubts with others, especially the course staff. That way you will get the most out of the discussion.
It is important to keep in mind the limits to collaboration. As noted above, you and your friends are encouraged to discuss course content and approaches to problem solving. But you are not allowed to share your code or answers with other students. Doing so is academically dishonest, and it also doesn't help them: it just sets them up for trouble on the next assignment and on exams.
You are also not permitted to turn in answers or code that you have obtained from others. Not only is such copying dishonest, it misses the point of the assignments, which is not for you to find the answers somewhere and send them along to the staff. It is for you to figure out how to solve the problems, with the support available in the course.
All you have to do is ask staff for help when you need it. You are not alone in this course! Instructors and Coaches are here to help you succeed. We expect that you will work with integrity and with respect for other members of the class, just as the course staff will work with integrity and with respect for you.
No collaboration on exams is allowed in any form. The following are guidelines on what non-exam collaboration is authorized and what is not:
What is Cheating?
What is not Cheating?
Academic accommodations are available for students registered with the Office for Accessibility and Educational Opportunity (AEO). Students in need of disability (ADA/504) accommodations should schedule an appointment with me early in the semester to discuss any accommodations for this course that have been approved by the Office for Accessibility and Educational Opportunity, as indicated in your AEO accommodation letter.
Vassar College is committed to providing a safe learning environment for all students that is free of all forms of discrimination and sexual harassment, including sexual assault, relationship abuse, and stalking. If you (or someone you know) has experienced or experiences any of these incidents, know that you are not alone. Vassar College has staff members trained to support you in navigating campus life, accessing health and counseling services, providing academic and housing accommodations, helping with legal protective orders, and more.
If you wish to speak to someone privately, you can contact any of the following on-campus resources: