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Learner Reviews & Feedback for Introduction to Recommender Systems: Non-Personalized and Content-Based by University of Minnesota

4.4
stars
659 ratings

About the Course

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....

Top reviews

DP

Dec 7, 2017

Nice introduction to recommender systems for those who have never heard about it before. No complex mathematical formula (which can also be seen by some as a downside).

IP

Sep 18, 2016

it's a fantastic course that gives you a good idea of what the objectives of recommender systems are and some intuition on the way how it can be accomplished.

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101 - 125 of 141 Reviews for Introduction to Recommender Systems: Non-Personalized and Content-Based

By SR T

Aug 3, 2017

first time taking a course using Coursera...material was very interesting and well explained. I wish there was a way to speed up the audio track a little to shorten the lecture length. hard for the lecturer to engage with an audience that is not there, but both tried to do so.

By Dhananjay G

Dec 21, 2019

I found this course very useful for me to get in to basics and back ground of recommendations. Each topic is presented and discussed quite in detail . I also found the interviews with various expert in Recommendations very insightful. Thanks you Joe and Micheal.

By Swetha P S

Oct 25, 2017

Very informative course! I had a great learning experience working on the programming assignments required for honors. The only drawback is the style of communication (written and spoken) is elaborate and confuses many non-native English speakers including me.

By Abhisek G

Jun 5, 2017

There is a need to have this course in Python or some other statistical programming language. Simple reason is that a lot of budding data scientists are not coming from CS background and dont have necessary skillset in Java. Else the course is good.

By rahul r

Jun 9, 2018

I think some of the interviews didn't really give me great insights. I know this is only an introduction, but I was expecting more fields than movies. I am overly critical though, all in all a very good way to understand recommendation systems.

By shailesh k p

Jun 22, 2018

I am very new to recommendation system and yet able to comprehend the lessons. The best thing is explaining the system with example. Walking through Amazon.com and explaining content based and collaborative filtering is easy to grasp.

By Diana H

Jul 29, 2017

I think it could be fun if there were simple assignments which could be done in python. Java can be a bit heavy and a lot of the time goes with figuring out the framework. :)

By nitish a

Apr 7, 2020

The course and its content was quite interesting and easy, so I will be taking the next course in this specialization of Recommender System Specialization

By Lucas B A d A

Apr 3, 2020

A complete introduction to the topic. Some interviews are lacking of audio and video quality. The assignments are pretty suitable to the content.

By Danish R

Oct 9, 2016

More information on Programming Assignment would have been helpful . Overall a good course to begin the specialization

By Atieno M S

Aug 16, 2019

The course was a good one with content that's understandable. I can't wait to proceed to the next one

By Wesley H

May 9, 2018

Great introduction to Recommender systems. Really got me thinking about how I could apply them.

By ignacio v

Feb 4, 2019

done it by audit, thnks!!! great stuff guys... but should do some practice in python!

By Lalu P L

Sep 19, 2022

Please update the specialization, it's 2022, and the course slides are from 2016.

By Reza N

Apr 27, 2017

The course was easy to understand. but i find the slides not much of help.

By Nitin P

Nov 18, 2016

I think this is a good course to start exploring recommendation systems.

By Ben C

Oct 29, 2017

I'd really like trying coding, but there's no Python option..

By Mehmet E

Jan 13, 2018

videos are too long... I had to watch them with x2 speed...

By Peter P

Oct 4, 2016

Too theoretical. I hope other parts will have more details.

By Aleshin A

May 18, 2018

It would be better to make practice on Python.

By Aladdin P

Oct 18, 2023

Would've liked honor to be in Python

By Ya W T

Oct 26, 2025

Content is too old

By Egbert R

Apr 11, 2021

Great course.

By Andre C

Mar 30, 2020

Great course

By Gabriel S

Feb 28, 2019

not so deep