Introduction to Recommender Systems: Non-Personalized and Content-Based
Coursera
8 Courses
The University of Illinois at Urbana-Champaign is one of the leading public universities in the country, providing top-tier academic programs and research opportunities within a lively campus community.
Overview
Title: Introduction to Recommender Systems: Non-Personalized and Content-Based
Description: Kickstart your journey into the world of recommender systems with this introductory course, proudly offered by the University of Illinois at Urbana-Champaign through Coursera. Perfect for beginners, this course lays the foundational knowledge of recommender systems, including non-personalized recommendations through summary statistics and product associations, as well as demographic and content-based filtering recommendations. Enhance your skills further by utilizing basic spreadsheet tools to compute various recommendations, or advance your expertise by programming these recommendations with the LensKit toolkit in the honors track. Featuring in-depth lectures, interactive exercises, and exclusive interviews with renowned leaders in the field, this course dives deep into advanced topics and the latest trends in recommender systems. Ideal for individuals interested in expanding their knowledge in Artificial Intelligence and Recommender Systems.
University: University of Illinois at Urbana-Champaign
Provider: Coursera
Categories: Artificial Intelligence Courses, Recommender Systems Courses
Syllabus
Taught by
Joseph A Konstan and Michael D. Ekstrand