Artificial Intelligence has become pervasive in our society. The goal of this course is to impart some understanding of how AI works, i.e., to introduce the basic concepts, algorithms and technology underlying systems that employ AI in service of society's needs. The course objectives are to learn the fundamental theories, algorithms and representational structures underlying artificial intelligence. Class discussions will range from algorithm fundamentals to philosophical issues in Artificial Intelligence.
Here are the formally graded elements of the course and associated weighting:
|Programming Assignments (5-6)||45 %|
|Canvas Quizzes||10 %|
Semester grades are determined by the weighted sum of points earned in each of these areas.
The calculation of the final letter grade will be made as follows: A: 90 - 100% B: 80 - 89.9% C: 70 - 79.9% D: 60 - 69.9% F: below 60%
These ranges for a letter grade might be shifted a little lower, but will not be raised. Your weighted average of score on the exam must be ≥60% to receive a passing grade (C) in this course.
Exams and homework assignments will be done individually.
Midterm and Final: Make-up exams are only given in extraordinary circumstances (e.g., illness, family emergency). Students must consult with the instructor as soon as possible, preferably before the start of the exam. Course examination dates are listed in the syllabus; be aware of them and plan accordingly.
Assignments: Unless otherwise specified, assignments are to be submitted electronically through Canvas. Specifics will be included in each assignment. Always check the assignment page for due dates. Late assignments submitted within 48 hours of the time required will receive a 10% late penalty. Electronic submission is closed 48 hours after assignments are due; students not having submitted programs receive an automatic zero on the assignment.
|End of course withdrawal ("W") period||Oct 21st|
The midterm will be held in class.
All students are expected to conduct themselves professionally. We (the instructors and GTAs) assume you are familiar with the policies in the student information sheet for the department. Additionally, you are computing professionals, albeit perhaps just starting. You should be familiar with the code of conduct for the primary professional society, ACM. You can read the ACM Code of Conduct HERE.
We work to maintain an environment supportive of learning in the classroom and laboratory. Towards that end, we require that you be courteous to and respectful of your fellow participants (i.e., classmates, instructors, GTAs and any tutors). In particular: