Who is this class for: This course is appropriate for learners who have a basic understanding of statistics. It can be useful both for those exploring applied machine learning and data mining, and for those focused on technology-supported marketing and commerce.


Created by:   University of Minnesota

  • Joseph A Konstan

    Taught by:    Joseph A Konstan, Distinguished McKnight Professor and Distinguished University Teaching Professor

    Computer Science and Engineering

  • Michael D. Ekstrand

    Taught by:    Michael D. Ekstrand, Assistant Professor

    Dept. of Computer Science, Boise State University
Basic Info
Course 1 of 5 in the Recommender Systems Specialization.
LevelIntermediate
Commitment4 weeks; an average of 3-7 hours per week, plus 2-5 hours per week for honors track.
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.5 stars
Average User Rating 4.5See what learners said
Syllabus

FAQs
How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers
Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates
Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creators
University of Minnesota
Pricing
AuditPurchase Course
Access to Course Materials

Available

Available

Access to Graded Materials

Not available

Available

Receive a Final Grade

Not available

Available

Earn a Shareable Certificate

Not available

Available

Ratings and Reviews
Rated 4.5 out of 5 of 93 ratings

Excelente curso, presenta una vista amplia de técnicas para la implementación de sistemas de recomendación, lo recomiendo totalmente.

Un profesor excelente y un temario muy bueno. También me han gustado mucho las entrevistas y los recorridos por las páginas web que tienen recomendadores.

Exceptional quality.The course content is comprehensive and practical enough applied at workplaces.

Guest lectures are super helpful and assignments are very practical yet make you think.

Thank you Coursera and Minnesota professors for this amazing course and wonderful opportunity for people like me with no background in recommendation systems learn the best research methods and practices in this field.

As a software engineer with computer science background I found that course enhancing my knowledge. I'm going to continue the specialization.