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Recommender Systems (CI11009)

General information

Type:

 OP

Curs:

 1

Period:

 S semester

ECTS Credits:

 3 ECTS

Teaching Staff:

Group Teacher Department Language
Marc Torrens Arnal Operaciones, Innovación y Data Sciences ENG

COURSE CONTRIBUTION TO PROGRAM

Few implementations of Artificial Intelligence have been so popular and so widespread as recommender systems. Almost every e-commerce company uses them, but not only e-commerce, we can find them in knowledge sharing, music, movies, ? almost everywhere.

Understanding their capabilities and limitations together with being able to leverage on existing libraries to build one is an important asset in the field.

Course Learning Objectives

After finishing this subject, participants should be able to:

1) Have a good understanding of the different types and capabilities of recommender systems.
2) Have a clear view of the business side of recommendation and how it can be used to boost business performance.
3) Be able to leverage existing libraries to build one with minimum coding.

Assessment criteria

Course Assessment will take in consideration three aspects:

1) Attendance and participation.
2) Theoretical understanding of the subject from both business and technical perspectives.
3) Capacity of leveraging existing libraries to build a simple recommender.

Timetable and sections

Group Teacher Department
Marc Torrens Arnal Operaciones, Innovación y Data Sciences

Timetable

From 2018/4/24 to 2018/6/5:
Each Tuesday from 15:30 to 18:30. (Except: 2018/5/1)