About this Course
3.8
12 ratings
4 reviews
This capstone project course for the Recommender Systems Specialization brings together everything you've learned about recommender systems algorithms and evaluation into a comprehensive recommender analysis and design project. You will be given a case study to complete where you have to select and justify the design of a recommender system through analysis of recommender goals and algorithm performance. Learners in the honors track will focus on experimental evaluation of the algorithms against medium sized datasets. The standard track will include a mix of provided results and spreadsheet exploration. Both groups will produce a capstone report documenting the analysis, the selected solution, and the justification for that solution....
Stacks
Globe

100% online courses

Start instantly and learn at your own schedule.
Calendar

Flexible deadlines

Reset deadlines in accordance to your schedule.
Clock

Approx. 7 hours to complete

Suggested: 1-3 weeks of study, 3-5 hours per week...
Comment Dots

English

Subtitles: English...
Stacks
Globe

100% online courses

Start instantly and learn at your own schedule.
Calendar

Flexible deadlines

Reset deadlines in accordance to your schedule.
Clock

Approx. 7 hours to complete

Suggested: 1-3 weeks of study, 3-5 hours per week...
Comment Dots

English

Subtitles: English...

Syllabus - What you will learn from this course

Week
1
Clock
4 hours to complete

Capstone Project

...
Reading
2 videos (Total 6 min), 2 readings, 3 quizzes
Video2 videos
Capstone Wrap-Up1m
Reading2 readings
Capstone Assignment (all versions combined)10m
Thank you!10m
Quiz1 practice exercise
Certification for honors track2m

Instructors

Michael D. Ekstrand

Assistant Professor
Dept. of Computer Science, Boise State University

Joseph A Konstan

Distinguished McKnight Professor and Distinguished University Teaching Professor
Computer Science and Engineering

About University of Minnesota

The University of Minnesota is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations....

About the Recommender Systems Specialization

This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative techniques. Designed to serve both the data mining expert and the data literate marketing professional, the courses offer interactive, spreadsheet-based exercises to master different algorithms along with an honors track where learners can go into greater depth using the LensKit open source toolkit. A Capstone Project brings together the course material with a realistic recommender design and analysis project....
Recommender Systems

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.