Project in Learning Systems (236757) - Winter semester, 2017

Instructor: Ran El-Yaniv

Prerequisite: Any credited machine learning course offered at the Computer Science department. Possible substitutes: machine learning courses from the Electrical Engineering or Industrial Engineering Departments.


Description: In this course, the students will engage in mini-research projects conducted in small teams of 1 to 4 students. Under the guidance of the instructor, and in conjunction with the students' skills and interests, each team be offered a project by the instructor. Alternatively, the team can propose a topic (that will have to be approved by the instructor). Typically, the project will be defined after a brainstorming meeting together with the instructor. The goal of this course is to deepen the knowledge and understanding of specific topics in machine learning and increase students' proficiency in utilizing machine learning tools to solve interesting problems. The projects are designed to include small research components including writing a mini research proposal, conducting a brief literature review, designing and defining benchmark tests and writing a summary report. Each team will conduct periodic meetings with the instructor. In these meetings the team will report on their progress and present the obstacles and problems encountered. Guided by the instructor, the team will plan their next steps and short term goals. The course is offered to both undergraduate and graduate students.
Registration: Please don't try to register on your own. This course is "manual registration" (registration done by the instructor). The course is open to a limited number of students from all faculties who have the required machine learning prerequisite. Among the interested students we will select at most 8 teams (each consisting of 1-3 students), based on course /work history and grades profiles. If you are interested to apply, please email grade transcripts + CV to with subject line: "applying to 236757".  If you have a team, please bundle your application for all team members together.  Send your application by email until October 7th. We will notify  potential acceptance to everyone by October 14th  and then schedule individual meetings with each selected teams during the weeks Oct 14th-October 26. You can apply even if you are not completely sure about this course and then if your team is selected, you can finalize your decision about registration after the first meeting.

Important dates
    Application ends: October 7th, 2017 (send grade transcript +CV for all team members)
    Team selection: October 14th, 2017 (notification by email)
    First meetings with teams: First week of the semester - Oct 21-25, 2017