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
Hardware ReqFor honors track must be able to run substantial computations using Java (e.g., 4GB or more ram).
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
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.
Pricing
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Access to graded materials

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Receive a final grade

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Earn a shareable Course Certificate

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Ratings and Reviews
Rated 4.5 out of 5 of 128 ratings

great!! Let me better understand the research and practical fields!

Well prepared course. In-depth lecture. Easy to follow even when listening only. The course lectures is very detailed, and that is one thing I really liked. The videos does feel a bit long, and maybe we can chop it to smaller sub-topics.

The interviews are very interesting and show a glimpse of broader universe of recommendation system. However, the concepts explained in the interview is a bit hard to follow, as there is no accompanying presentation materials and it jumps to detailed content with little context

The regular exercise feels very easy but helpful to make the concepts concrete. The Honors programming exercise looks interesting & challenging, but it seems too hard for someone with no programming background. I am also learning Python in parallel, so I decided to drop it to avoid learning 2 languages in parallel.

Excellent course taught in simple language.

An excellent in-depth introduction into the concepts around recommendation systems!