*subject to minor changes and adjustments
  • Lectures by Alex and me

  • Homeworks

  • Projects

  • No midterm, no final exam

  • Class more like a research seminar but with lectures

  • The lecture plan will be made available online


  • Alex and I will cover a variety of topics there will be nontrivial connections between our coverage, but I would still view the course as “selected topics in mathematics of data science”

  • Lectures will be scribed, more about that in a minute

  • Scribing carries 2% credit

  • Approximately 8 short homeworks (every 2-3 weeks)

  • Homeworks count for 45% of the grade

  • Homework policy: collaboration is allowed, but solutions must be written up by you

  • We will run homeworks and the rest of the class like a research conference (treat the lectures as “tutorials”)

  • Everything will be handled via Easychair
    Sign up at:

  • Homeworks will be peer-reviewed

  • 5% of total grade depends on quality of job you do on easychair (answer key will be provided)

  • 1 day late: 50% credit lost on homework

  • More than 1 day late: 100% credit lost

  • Each project should have 2-4 people

  • Ideal team size: 3

  • It is important to team up: we wish to encourage experience in collaborative work

  • Entire team will get same grade, so pick team wisely (regardless of who did what percentage of work)

  • The projects are going to be divided into several easy phases

  • Initial proposal (2 pages); Who? Why? Etc. (2%)

  • Project midterm review (10% credit) (written report, peer-review part, approx 4 pages)

  • Final report – 8 pages + refs (25%)

  • Final presentations (8%, 10 mins long per project)

  • 3% credit for reviews

  • More detail to be avail very soon on the class webpage

  • Scribing: 2%

  • Homeworks: 45 + 5 = 50%

  • Projects: 48%