Mode: Online synchronous (i.e., location is online). The course will be delivered over Zoom (an invite will be sent before the first day of class). See the online learning page for basic technology requirements.
Any OS should be okay. If in doubt, run a virtual machine running linux (this will be discussed in the class). Some of the software we will work with are:
These involve reimplementing recent deep-learning techniques and understanding their behavior on interesting datasets. Always mention any sources that were relied on, in your assignment solutions. Submission deadline is BEFORE 11.59 PM on the concerned day. Late submissions will have an automatic 20% penalty per day without exceptions. Use Blackboard for uploads.
Project
Students are expected to apply what they learn in the course and demonstrate their understanding by undertaking a suitable project. A preliminary documentation along with the scripts/codes/commands used is to be submitted on October 7th and a final version of the same is to be submitted on December 2nd. The projects will be presented to the rest of the class on December 3rd. The evaluation criteria and other details are available here. Submission deadline is BEFORE 11.59 PM on the concerned day. Late submissions will have an automatic 20% penalty per day. Use Blackboard for uploading your work as a single zip file.
Grades
Grades will be based on the assignments (4 times 10%), the project (see project evaluation criteria above) (50%) and course participation (10%).
Miscellaneous Information
This is a 4 credit graduate level course offered by the Information and Decision Sciences department at UIC.
Students who wish to observe their religious holidays (http://oae.uic.edu/religious-calendar/) should notify the instructor within one week of the first lecture date.
Contact the instructor at the earliest, if you require any accommodations for access to and/or participation in this course.
Refer to the academic integrity guidelines set by the university.