Content-Based Filtering Courses and Certifications

Building Recommendation Engines with PySpark

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Building Recommendation Engines in Python

Learn to build recommendation engines in Python using machine learning techniques.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Microcredential

Recommendation Systems Theory and Coding

Master collaborative filtering, content-based methods, and hybrid techniques to build recommendation systems from scratch with hands-on projects and real-world applications.

• CodeSignal
• 15 hours
• On-Demand
• Free Certificate
• 4 courses

Content-Based Recommendation Systems

Dive into content-based recommendation systems, exploring factorization machines and DSSM with hands-on coding examples for developing personalized recommendation models using rich data.

• CodeSignal
• 4 hours
• On-Demand
• Free Certificate

Microcredential

Recommendation Systems Theory and Coding in JS

Master collaborative filtering, content-based methods, and hybrid techniques to build recommendation systems from scratch using JavaScript through hands-on projects.

• CodeSignal
• 15 hours
• On-Demand
• Free Certificate
• 4 courses

Content-Based Recommendation Systems using JS

Master content-based recommendation systems using JavaScript, from basic item profiling to advanced factorization machines for personalized recommendations.

• CodeSignal
• 4 hours
• On-Demand
• Free Certificate

Introduction to Recommender Systems: Non-Personalized and Content-Based

659 ratings at Coursera

Explore non-personalized and content-based recommender systems, learning techniques for product associations, demographic-based recommendations, and personalized filtering using user profiles.

• Coursera
• 23 hours 16 minutes
• On-Demand
• Paid Course

Recommendation Engine Bootcamp

158 ratings at Udemy

Master recommendation systems Industry Projects using using modern recommendation techniques and methodologies

• Udemy
• 4 hours 22 minutes
• On-Demand
• Paid Course

AI-Driven Marketing Personalization for Business Leaders

68 ratings at Udemy

Transform customer experiences with AI personalization: Learn algorithms, real-time data, and scaling strategies.

• Udemy
• 2 hours 6 minutes
• On-Demand
• Paid Course

EDUCBA Microcredential

Mastering Recommendation Systems with Python

69 ratings at Coursera

Master recommendation systems using Python, from collaborative filtering to hybrid models, with hands-on projects building movie and book recommenders using Surprise and Scikit-learn.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 4 courses

EIT Digital;  Politecnico di Milano

Basic Recommender Systems

43 ratings at Coursera

Explore leading recommender system approaches, from collaborative to content-based. Learn algorithms, evaluation techniques, and design strategies for personalized recommendations across various domains.

• Coursera
• 11 hours 50 minutes
• On-Demand
• Paid Course

EDUCBA

Project on Recommendation Engine - Advanced Book Recommender

25 ratings at Coursera

Master building personalized book recommendation systems using Python, combining collaborative and content-based filtering into hybrid models with real-world applications.

• Coursera
• 4 hours 37 minutes
• On-Demand
• Paid Course

EDUCBA

Project on Recommendation Engine - Book Recommender

11 ratings at Coursera

Discover how to build a functional book recommendation engine using Python, data science techniques, and content-based filtering to create personalized suggestions.

• Coursera
• 5 hours 15 minutes
• On-Demand
• Paid Course

EDUCBA

Develop a Movie Recommendation Engine

10 ratings at Coursera

Discover how to build movie recommendation systems using Python, from popularity-based models to content-based filtering with real-world data and machine learning techniques.

• Coursera
• 2 hours 52 minutes
• On-Demand
• Paid Course

Packt Microcredential

Recommender Systems

5 ratings at Coursera

Master advanced recommender systems using machine learning, deep learning models like RNNs and LSTMs, and build real-world recommendation engines with TensorFlow and Python.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 4 courses