Fairness in Machine Learning
INFSCI 2915 @ PITT
Welcome to the course page of Fairness in Machine Learning (official course name: FATE – Fairness, Accountability, Transparency, and Ethics in AI). This course is currently offered by Dr. Yu-Ru Lin in Fall 2024 at School of Computing and Information, University of Pittsburgh.
Basic information
- Course name: INFSCI 2915 Fairness in Machine Learning (Fall 2024)
- Canvas link: Coming Soon!
- Class Meeting Time: Tuesday 9:00 am - 11.40 am
- Meeting Place: IS 406
- Instructor: Dr. Yu-Ru Lin
- Teaching assistants: see Canvas
Communication & Email policy
We will regularly post announcements on Teams related to schedule changes, assignments, graded quizzes, follow-ups to lectures, INFSCI-2915 and other school or department-related activities.
Instead of email the instructor or TAs individually, please follow the class communication policy:
- Ask questions publicly: In general, all questions about coursework, course logistics, etc. should be asked publicly on Teams channels. If you ask such a question privately, we will not answer it: we will ask you to post your question publicly, and will answer it once you do. This way, everyone can benefit from the answer to the question and, if someone runs into the same issue you do, we can refer them to the answer we provided in your post.
- Communicate private matters: If you need to ask a private question, you can send an email to yuru-class-fairness-ml [at] googlegroups [dot] com. Your email will be seen only by the instructor and TAs. This should be used only for truly private matters that relate uniquely to you (e.g., you need to notify us of a family/medical emergency, etc.).
Syllabus
See the Fall 2024 syllabus.
Course Schedule
See the tentative course schedule.
Computing
This course will use R and/or Python for computing. GitHub will be used for homework and project assignments, where tools such as Jupyter Notebooks or R Markdown will be used for creating reproducible data science documents.
This website is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.