Classes: F 10-12 in Rosebrugh 310
Instructor: Michael Brudno
Office: Pratt (PT) 286C
Office Hours: By appointment
The prerequisite is an undergraduate-level understanding of Computer Science. While I do not expect that you would have familiarity with all computational concepts we discuss, you should be able to quickly "catch up" on the relevant topics. Solid understanding of artificial intelligence (especially machine learning), algorithms, and basic statistical concepts (e.g. p-values, multiple testing correction) will be needed for for multiple parts of the course
Grading:
The basic requirements for the class will be a course project (60% of the
grade), paper presentations and participation (20% of the grade) and written
paper summaries (20% of the grade).
The whole point of the paper summaries is to make sure that you've read the papers before coming to class, so no late summaries will be accepted.