Pratt Institute School of Information (http://si.pratt.edu) seeks a visiting assistant professor to teach INFO 697 Machine Learning. This graduate course is an elective in our Master of Science programs in Data Analytics & Visualization, Library & Information Science, Museums and Digital Culture and Information Experience Design.
[Course Description] Machine learning is a rapidly growing field that develops algorithms for tasks such as data classification and prediction. These algorithms are programmed to operate and adjust themselves independently of human intervention (i.e., to learn), allowing data work to occur quickly and at scale. This course will survey supervised methods for machine learning (regression and classification), which attempt to map data onto desired outputs, and unsupervised methods (clustering and association), which attempt to find structure within data itself. Students will learn how to implement machine learning techniques on text and image data, assess the effectiveness of different techniques on particular datasets, and discuss basic issues that confront all machine learning methods.
[Student Learning Outcomes] By the end of the course, students will be able to:
● describe different machine learning methods, including their biases and limitations
● select an appropriate machine learning method for a given use case
● implement machine learning algorithms and assess their performance
The course is offered August 27 to December 10 on Tuesdays 6:30pm-9:20pm at Pratt Manhattan Center – 144 W. 14th St. near 7th Avenue.
The candidate should have a Master’s degree in a relevant field and have an aptitude for teaching. The applicant will receive compensation for developing the syllabus as well as teaching the course.
For questions about the course and to apply, please email Dean Anthony Cocciolo – acocciol@pratt.edu.
Deadline for application is Friday, March 15, 2019.
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