Salman

Recipients of Uplimit Personalized Recommendations certificates have learned a holistic overview of ML modeling choices that go into developing and deploying multi-stage recommenders capable of serving recommendations from hundreds of million content choices to multiple hundred million users. They dove into algorithmic models that power the various stages of the recommender, including the candidate generator, core ranker, user representation learning modules and offline and online evaluation module.

Certification criteria:

Actively participated in Uplimit's dynamic course on Recommendations: attended lectures, lab sessions, Fireside Chats with industry leaders, and more.

Built projects that use multi-stage composition of large scale recommender, ML approaches for ranking and recommendations, online learning from user interactions, and measured using offline, online & counterfactual evaluation

August 10, 2022 Instructor: Rishabh Mehrotra

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Developed familiarity with fundamentals of case studies, lessons and practical considerations from deployed recommendations systems powering over 400 million users.