Building Llm-Powered Recommendation Systems
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![[Image: e709b1e5872147074f2c876df42848d8.png]](https://i126.fastpic.org/big/2026/0206/d8/e709b1e5872147074f2c876df42848d8.png)
Building Llm-Powered Recommendation Systems
Released 2/2026
With Rishabh Misra
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 18m | Size: 252 MB[/center]
Learn how to design, build, evaluate, and deploy production-ready recommender systems that leverage the power of GenAI for enhanced personalization, quality, and user trust.
Course details
Get a technically grounded overview of how to start building the next generation of intelligent recommender systems. Moving beyond traditional algorithms, this course shows you how to immediately enhance existing systems by applying AI-powered techniques for embedding generation, semantic reranking, cold start mitigation, and more. Instructor Rishabha Misra outlines the essentials of designing sophisticated, GenAI-native architectures that enable dynamic experiences like conversational search and multimodal recommendations. An ideal fit for software engineers, data scientists, AI and ML engineers, and technical product managers, this course focuses on robust evaluation, teaching you how to measure for quality and fairness and ensure factual accuracy through patterns like retrieval-augmented generation (RAG). By the end of this course, you'll be prepared to design, evaluate, and operationalize effective and responsible GenAI recommender systems in a production environment.
Skills covered
Large Language Models (LLM), Recommender Systems
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