Advanced Recommender Systems at Polytechnic University of Milan, Milan

Advanced Recommender Systems Certification Programme is an intermediate-level course for eligible learners who want to brush up on their machine learning knowledge and learn more about recommender systems. It will enhance the knowledge of learners by teaching them the following-

• Candidates will be able to adopt machine learning in collaborative filtering techniques.
• They will learn how to use factorisation machines while representing the input data and mixing various kinds of filtering techniques.
• They will be able to mark the difference between model-based and memory-based and recommender systems along with their pros and cons.
• They shall also learn how basic approaches combine to form a hybrid recommender system that improves the quality of recommendations.
• Learners shall learn to define a new error metric based on ranking comparisons that shall play an instrumental role in designing learning-to-rank algorithms.
• Machine learning and neural network techniques will be taught in detail to design more sophisticated recommender systems.
• Learners will know how to balance input information using coefficients and weights for creating more sophisticated predictions.
• They will be able to integrate many kinds of side information (about content or context) in a recommender system.
• Candidates shall study different simple and complex hybridisation approaches.
• They shall get a practical insight on how to choose the accurate number of latent features to reduce the risk of overfitting historical data.