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.


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July 2025
7 项作业
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该课程共有2个模块
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.
涵盖的内容
9个视频4个作业
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.
涵盖的内容
6个视频3个作业
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University of Minnesota
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EIT Digital
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已于 Aug 10, 2025审阅
Practical, engaging project for building book recommendation system.
已于 Aug 20, 2025审阅
Effective book suggestions using user preferences and similarity algorithms.
已于 Jul 20, 2025审阅
Practical project showcasing book recommendations using real-world data and techniques.
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When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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