Recommender Systems with AI: From Collaborative Filtering to Deep Learning

A premium, complete and hands-on course on modern recommender systems, updated for 2026. You will start from why recommendation is one of the highest-leverage applications of machine learning, then build up every major family of models with real Python code. You will master content-based filtering with TF-IDF and embeddings, memory-based collaborative filtering (user-based and item-based neighborhoods), and matrix factorization with SVD, ALS and Bayesian Personalized Ranking using the implicit and LightFM libraries. You will learn the crucial difference between explicit and implicit feedback and why it changes both your model and your loss. From there you will build deep learning recommenders — neural collaborative filtering, embeddings, and the two-tower retrieval architecture — and sequential and session-based models with self-attention (SASRec, BERT4Rec). You will design the two-stage candidate-generation-plus-ranking architecture that powers recommendation at scale, serve it with approximate nearest neighbor search, and solve the cold-start problem. You will evaluate systems correctly with precision@k, recall@k, MAP and NDCG, understand why offline and online metrics diverge, and run trustworthy A/B tests. The final modules cover how large language models reshape recommendation in 2026, how to build for diversity, serendipity and fairness, and how to stay compliant with the GDPR when you profile user behavior. Includes a comprehensive final assessment. This deepened edition adds factorization machines, graph neural networks (LightGCN, PinSage), multi-armed and contextual bandits with off-policy evaluation, and a dedicated lesson on the EU Digital Services Act's recommender transparency duties - around 30 in-depth lessons of university-level, practice-first material.

The course has 11 modules and 30 lessons, with 355 quiz questions. The full curriculum, module by module, is shown on the course page.

Yes. The course is Advanced level and assumes hands-on experience with AI in its field.

The estimated duration is about 25 hours, across 30 lessons. You learn at your own pace, and your progress is saved automatically at every lesson, so you can pick up where you left off.

Access to this course alone costs €99 per month. The course is also included in the IT Pro bundle, €399 per month for all 25 IT Pro courses, and in All Access, €499 per month for the whole international catalog.

Plans are billed monthly, in EUR. Every price is a total, with VAT included at the rate of your country. Compare the plans.

Yes. You can read a free preview of lesson 1, “Why Recommender Systems Matter in 2026”, without an account. The preview shows you how the lesson is written; the rest of the lesson and the other lessons open after payment.

The AI Professor is built into every lesson and starts from the lesson you have open: it explains the passages you select, gives you examples, summarizes the lesson, tests you with a quiz and prepares review flashcards. You can type or talk to it, in English.

It is included in your subscription, per-course access included, with a monthly fair-use limit. It is an AI system, not a human teacher, and its answers may contain errors; details in the Terms.

When you meet the completion thresholds shown on the platform (lessons completed and the minimum quiz score), you can issue your Certificate of Completion for “Recommender Systems with AI: From Collaborative Filtering to Deep Learning” from your account, with a unique number, publicly verifiable on the site.

It is a private attestation of course completion, issued by GALIAN SOFTWARE DEVELOPMENT SRL. It is NOT a diploma or a state-recognised qualification under Romanian Laws 198/2023, 199/2023 or Government Ordinance 129/2000; employers may take it into account at their own discretion. Details in the Certification policy.

Yes. Course access and the bundles are subscriptions that renew automatically at the end of each monthly billing period. You can see the next renewal date in your account at any time.

You can stop the renewal at any time, from your account or by email, with no other formality. Access stays active until the end of the period already paid for, and no pro-rata refund is made for a period already started, except in the cases provided by law. Your progress stays saved in your account. Details in the Terms & Conditions, section 5.5.

Yes. Company plans give a team access to the courses, with a dashboard where you follow each member’s progress and manage seats centrally. See the plans for companies.