Principles and programming techniques of artificial intelligence: Python, symbol manipulation, knowledge representation, logical and probabilistic reasoning, learning, language understanding, vision, expert systems, and social issues. Not open for credit to students who have completed 473.
Prerequisites: CSE 373.
Lecture for this course is help Monday, Wednesday, and Friday, 1:30-2:20pm. Students are strong encouraged to attend in person. However, lectures will be recorded and available via Panopto on Canvas. Students who are feeling unwell as asked to stay home and review the recorded material.
Office hours will be available both remotely and in person. The office hours sechedule is currently still to be determined; please refer to the schedule tab o this webpage. Zoom links will be available through Canvas
Schedule updates, modifications, and details will be available via the schedule tab of this webpage.
The strongly recommended text book for this course is Artificial Intelligence: A Modern Approach, by Stuart Russell & Peter Norvig, Prentice-Hall, Fourth Edition (2020) [R&N]. Regular reading assignments from this text will be recommended.
There are a number of additional recommended texts, as well as other resources, available under the resources tab of this webpage.
Assignments for this course are comprised of written homeworks (6) and programming projects (4). Homeworks and projects are weighted equally for the final grade, and are intended to be completed independently. These assignments are graded on correctness. Most lectures will include practice problems which review the material and recieve credit upon submission. In addition to this work there will be assigned reading, which is not evaluated but will enhance student mastery of the subject.
There are no traditional exams offered in this course.
More details about assignment specifcs and the grading policy may be found on the assignments tab of this webpage.
This course follows University and CSE guidelines for academic integrity. Any attempt to misrepresent the work you submit will be dealt with via the appropriate University mechanisms, and your instructor will make every attempt to ensure the harshest allowable penalty. The guidelines for this course and more information about academic integrity are in a separate document (CSE misconduct). You are responsible for knowing the information in that document. Please notice that you should not, in any situation, borrow another person's code or provide yours to a fellow student, including students in other quarters of this course. You also will refrain from sharing problem sets and answers with students from other quarters, and following assignment guidelines on group work.
This course adheres to University standards including those guidelines laid out about Academic Integrity and Student Conduct. We refer students to support and accommodation services including Disability Services, Religious Accommodations, and Safe Campus resources.
In acknowledgement of the ongoing pandemic, we are committed to providing remote access for those times it is necessary, and flexible scheduling to the extent that it is possible. We request that students remain home when sick and consider masking in indoor spaces, as per UW Policy. We encourage all students to care for their physical and mental health, and to reach out if further accommodations are necessary.
This instructor seeks to ensure all students are fully included in each course, and strives to create an environment that reflects community and mutual caring. I encourage students with concerns about classroom or course climate to contact me directly (mh75 at uw.edu). In the event you are more comfortable with a different approach, please refer to the resources above.