About this Course

Flexible deadlines
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Shareable Certificate
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100% online
Start instantly and learn at your own schedule.
Intermediate Level

Python programming, data structures, algorithms, linear algebra, calculus, and information theory are prerequisites, but not strongly required.

Approx. 17 hours to complete
English

What you will learn

  • ​Understand the basic concept of recommender systems.

  • ​Understand the Collaborative Filtering.

  • ​Understand the Recommender System with Deep Learning.

  • ​Understand the Further Issues of Recommender Systems.

Skills you will gain

  • Tabular data handling with python programming
  • Performance evaluation skills for recommender systems
  • Building recommender systems based on collaborative filtering
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level

Python programming, data structures, algorithms, linear algebra, calculus, and information theory are prerequisites, but not strongly required.

Approx. 17 hours to complete
English

Offered by

Placeholder

Sungkyunkwan University

Syllabus - What you will learn from this course

Week
1
Week 1
4 hours to complete

Introduction to Recommender Systems

4 hours to complete
3 videos (Total 47 min), 3 readings, 3 quizzes
Week
2
Week 2
4 hours to complete

Collaborative Filtering

4 hours to complete
3 videos (Total 43 min), 3 readings, 3 quizzes
Week
3
Week 3
4 hours to complete

Recommender System with Deep Learning

4 hours to complete
3 videos (Total 48 min), 3 readings, 3 quizzes
Week
4
Week 4
4 hours to complete

Further Understanding of Recommender Systems

4 hours to complete
3 videos (Total 37 min), 3 readings, 4 quizzes

Frequently Asked Questions

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