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Basic Recommender Systems

Learners:

Instructor: Paolo Cremonesi

Duration: 12.00

This course introduces you to the leading approaches in recommender systems. After completing it, you'll be able to design recommender systems tailored for new application domains, also considering surrounding social and ethical issues. You'll learn how to distinguish recommender systems according to their input data, their internal working mechanisms, and their goals. You'll also have the tools to measure the quality of a recommender system and to incrementally improve it with the design of new algorithms. Unleash your creativity and innovation skills to design a new recommender system and improve the quality of the predictions. Click now to learn more!▼▲

Course Feature Course Overview Course Provider

Go to class

Course Feature

Cost:

Free

Provider:

Coursera

Certificate:

Paid Certification

Language:

English

Start Date:

10th Jul, 2023

Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 27th, 2023]

This course introduces students to the leading approaches in recommender systems. Students will learn about the most important algorithms used to provide recommendations, how they work, how to use and evaluate them, and the benefits and limits of different recommender system alternatives. Upon completion of the course, students will be able to describe the requirements and objectives of recommender systems based on different application domains, distinguish recommender systems according to their input data, internal working mechanisms, and goals, measure the quality of a recommender system, and design recommender systems tailored for new application domains, considering surrounding social and ethical issues such as identity, privacy, and manipulation. Additionally, this course leverages two important EIT Overarching Learning Outcomes (OLOs), related to creativity and innovation skills. Students will be encouraged to think beyond boundaries and use knowledge, ideas, and technology to create new or significantly improved recommendation tools to support choice-making processes and strategies in different and innovative scenarios, for a better quality of life.