Introduction to Recommender Systems: Non-Personalized and Content-Based
$79
ENROLL NOWCourse Overview
This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. After completing this course, you will be able to compute a variety of recommendations from datasets using basic spreadsheet tools, and if you complete the honors track you will also have programmed these recommendations using the open source LensKit recommender toolkit. In addition to detailed lectures and interactive exercises, this course features interviews with several leaders in research and practice on advanced topics and current directions in recommender systems.
Course FAQs
What are the prerequisites for 'Introduction to Recommender Systems: Non-Personalized and Content-Based'?
Prerequisites for this continuing education class are set by University of Minnesota. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.
Will I receive a certificate for this CE class?
Yes, upon successful completion, University of Minnesota typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.
How long does this online course take to complete?
Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.
