ELE520: Mathematics of Data Science

Yuxin Chen, Princeton University, Fall 2020


  • Yuxin Chen, C330 Equad, yuxin dot chen at princeton dot edu

  • Office hours: Tue/Thu 11am - 12pm (after the lectures), Zoom (see Blackboard), or by appointment

Teaching Assistants

  • Changxiao Cai, ccai at princeton dot edu

    • Office hours: Fridays 4pm-5pm, Zoom (see Blackboard), or by appointment

  • Yanxi Chen, yanxic at princeton dot edu

    • Office hours: Thursdays 5pm-6pm, Zoom (see Blackboard), or by appointment

Lecture Times

  • Tue, Thu 9:30 AM - 10:50 AM

Administrative Assistant


  • Homeworks. There will be a few homework assignments that involve both theory and programming components. No late homeworks are accepted. You are encouraged to use LaTeX to typeset your homeworks.

  • Final project. See the description here.

  • Your grade: max{ 0.4*Homework + 0.6* Project, Project }

Course Policies

  • Prerequisites. Students should have backgrounds in basic linear algebra and in basic probability (measure- theoretic probability is not needed), as well as knowledge of a programming language like MATLAB or Python to conduct simple simulation exercises. While no specific background in optimization is required, a course such as ORF307 (Optimization) would be beneficial.

  • Piazza. The main mode of electronic communication between students and staff, as well as amongst students, will be through http:www.piazza.com/. It is intended for general questions about the course, clarifications about assignments, student questions to each other, discussions about material, and so on. We strongly encourage students to participate in discussion, ask and answer questions through this site. The course staff will monitor discussions closely.

  • Collaboration. We encourage you to work on homework problems in study groups. However, you must write up and submit your own solutions and code without reading or copying the solutions of other students or other online resources.