Artificial Intelligence Research
and Education
PhD Qualifying Exam
The AI Depth Exam is designed to test for both a general "breadth" knowledge
of AI, plus a deeper specialized knowledge of one particular
sub-area within AI. The current sub-areas tested for, and the
corresponding courses, are: machine learning (CS
760) and computer vision (CS
766).
Students will be required to specify their sub-area when they
sign up for the exam, and then answer corresponding questions in
that sub-area, as described in detail below. Passing the exam
will then be considered as demonstration of competence in that
particular sub-area, so that except in unusual circumstances, the
student will be expected to pursue Ph.D. research in the area chosen.
Students will be prepared for the AI Exam if they have mastered
(a) the material presented in an introduction to artificial intelligence
course such as CS
540;
(b) the material presented in at least two of
731,
760,
766,
776,
and 769;
(c)
the Basic and the Advanced Readings associated with one of CS 760
and 766; and (d) the Basic Readings for at least one additional class
chosen from CS 731, 760, 766, 776, and 769. Students should note that
the Advanced Readings go beyond the material covered in the associated
course. The introductory AI material (CS 540) will not be tested
in separate questions, but knowledge of this subject
matter is likely to prove necessary when answering the graduate (700)
level questions.
The AI Examination will consist of questions in six separate sections.
There will be two "basic" questions in each of sections B731, B760,
B766, B776, B769, and two "advanced" questions in each of sections A760
and A766. To pass the examination, students will have to answer satisfactorily
both of the questions in one of the A sections (A760 or A766); both
of the questions in the B section (B760 or B766) for the same sub-area;
and two additional questions from any of the other B sections. The
two additional questions can be but do not have to be from the same
section. The A section chosen must correspond to the sub-area for
which the student is signed up.
The advanced questions focus on principles and concepts, and the
student is expected to be able to solve new and original problems
which require adapting the material covered in the reading lists
below. The questions answered by the student will not in general
be weighted equally. In particular, students will not pass unless
they have demonstrated competence in their chosen specialty.
Reading Lists
Previous AI Qualifying Exams
Postscript or PDF versions of old AI qualifying exams are
on-line at the
department's archive
of Ph.D. Qualifying Exams.
This page was created by palmeran@biostat.wisc.edu
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