Data Science: An Artificial Ecosystem

Harvard Summer School

STAT S-115

Section 1

CRN 35611

View Course Details
This course aims to introduce students to the world of the data science via articles published in the Harvard Data Science Review, a global forum disseminating everything data science and data science for everyone. The course emphasizes the evolutionary nature of the data science enterprise as an artificial ecosystem, where the phrase artificial shares a similar connotation as it is in the phrase artificial intelligence (AI). However, unlike the common algorithmic or robotic depictions of AI, this course espouses a panoramic view of data science, from philosophical conceptualization of data to interpretation and policy implications of statistical findings and to the re-use of data for addressing scientific replicability and reliability. Topics such as generative AI and data privacy are explored in depth to demonstrate the necessity of the panoramic approach. Questions such as what is intelligence or what is privacy require philosophical contemplation, while assessing the impact of generative AI or means to protect individual privacy demand careful sociological, computational, and statistical thinking. Furthermore, determining how to ensure effective and safe human-computer interaction requires advanced data science theory and methods. Throughout the course, students engage with and critique a broad range of data science articles that incorporate perspectives from computer science, statistics, philosophy, social sciences, and other fields of study. During course meetings, there are opportunities to discuss some of these articles with the authors themselves.

Instructor Info

Xiao-Li Meng, PhD

Whipple V.N. Jones Professor of Statistics, Harvard University and Founding Editor-in-Chief, Harvard Data Science Review


Meeting Info

MW 12:00pm - 3:00pm (6/24 - 8/9)

Participation Option: Online Synchronous

Deadlines

Last day to register: June 20, 2024

Prerequisites

Students are not required to have any prior experience in computer science, statistics, or data science. The course assignments will assess students' ability to think critically and communicate effectively, rather than their computational or mathematical skills.

Notes

This course meets via web conference. Students must attend and participate at the scheduled meeting time. Harvard College students: This course is eligible for degree credit, but see important policy information.

Syllabus

All Sections of this Course

CRN Section # Participation Option(s) Instructor Section Status Meets Term Dates
35611 1 Online Synchronous Xiao-Li Meng Field not found in response. MW 12:00pm - 3:00pm
Jun 24 to Aug 9