| Course Policies | |
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CSE 415: Introduction to Artificial Intelligence The University of Washington, Seattle, Autumn 2017 | |
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Effective learning requires that each student be actively
engaged in the subject matter and activities of the course.
The course is structured to foster that engagement
in several ways, including working together as a community
on in-class activities,
and appropriate challenges in assignments and the project.
All the students in CSE 415, the teaching assistants, and the instructor form a community. As a community, we can work together to help each other learn. The first step in allowing this to happen is for each person to be present at class meetings. Regular attendance in class is strongly encouraged, and systematic absences will have a direct effect on the class-participation part of the course grade. As for most three-credit courses at the University of Washington, students are expected to devote approximately 9 productive hours to the course per week. Actual demands will vary with the material and individual student. Each student is required to stay up to date with assignments, in order for the class to work as a community. Assignments that involve significant programming will typically have somewhat forgiving lateness penalty schedules, with the default being 10 percent off if turned in up to one hour late, 20 percent off for up to one day late, 30 percent off for up to 3 days late, 40 percent off for up to 5 days late, and 50 percent off for up to a week late. No credit will be given for programs turned in more than one week late. Each student will have at least one opportunity to work in a partnership on an assignment to implement a demonstration of one or more techniques of artificial intelligence. Except when explicitly permitted, students are expected to turn in their own individually produced solutions to homework problems. Turning in the work of another as one's own is considered as a serious form of academic misconduct. The University has strict rules and penalties that apply when evidence of such misconduct is found. The following is a tentative formula for weighting the various course components for computing final grades:
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