This hands-on project-based course guides learners through the process of designing, developing, and evaluating a functional Book Recommendation Engine using Python and data science techniques. Beginning with foundational principles, learners will identify key components of recommender systems, prepare structured datasets, and apply user-driven filters to generate personalized recommendations.
Project on Recommendation Engine - Book Recommender
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
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Recently updated!
July 2025
Assessments
7 assignments
Taught in English
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There are 2 modules in this course
This module introduces learners to the core principles of building a book recommendation engine using user-defined filters and structured data. Learners will explore initial project setup, data preprocessing techniques, and the application of foundational filtering logic based on publication metadata and user preferences.
What's included
9 videos4 assignments
This module advances learners into content-based filtering techniques by leveraging text features such as book title, genre, and description. Through the construction of similarity matrices and feature combination strategies, learners will implement a more intelligent and personalized recommendation engine.
What's included
6 videos3 assignments
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