Honors Colloquium for Introduction to Machine Learning

نظرة عامة على البرنامج

This colloquium explores the safety and fairness of machine learning algorithms, delving into examples of malfunctioning systems and algorithms designed to mitigate risks. Running from February to May, the course involves weekly meetings and culminates in a project where students train a machine learning model with safety and fairness considerations. Open to juniors and seniors in Computer Science or Informatics, department consent is required.

مخطط البرنامج

Outline:

• Content: This colloquium will delve into the safety and fairness of machine learning algorithms.
• Structure: Students will study examples of malfunctioning machine learning systems and explore algorithms designed to prevent such issues.
• Course Schedule: The colloquium runs from February 1, 2024 to May 10, 2024, meeting on Tuesdays from 4:00 PM to 4:50 PM in Computer Science Building room 140.
• Modules: The colloquium culminates with students training a machine learning model that incorporates safety and/or fairness guarantees.

Teaching:

• Teaching Methods: The colloquium is taught by Philip Thomas.
• Faculty: Philip Thomas is the instructor.
• Unique Approaches: The colloquium focuses on practical applications of machine learning, culminating in a project where students train a model with safety and fairness considerations.

Other:

• Eligibility: Open to seniors and juniors in Commonwealth Honors College majoring in Computer Science or Informatics.
• Prerequisites: Students must be enrolled in COMPSCI 389 (or have completed COMPSCI 389 with a grade of B or better).
• Department Consent: Department consent is required.
• Pass/Fail Option: No option for Pass/Fail.
• Override Request: Students can request an override via the online form: https://www.cics.umass.edu/overrides