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Generative AI and LLMOps: Building, Fine-Tuning, and Deploying LLMs https://WebToolTip.com Released 10/2026 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 2h 29m | Size: 259.29 MB Learn how to efficiently build, fine-tune, and deploy LLMs using a variety of methods, including retrieval-augmented generation and model compression. Course details Explore methods to optimize and deploy large language models (LLMs) for a wide range of applications. This course covers the selection of appropriate models, how LLMs process text and generate responses, and how to adapt models to specific applications through techniques such as prompt design, retrieval-augmented generation, and fine-tuning. Learn how to effectively manage model lifecycle from deployment in managed APIs to self-hosting or running on local devices. Discover how to leverage model compression techniques to optimize size and performance for local and edge deployment. Find out how to evaluate models using traditional metrics and advanced techniques like LLM judges. Develop strategies for robust and secure deployments while considering privacy and data governance. Transform AI capabilities in your work environment and beyond. whether you are a data scientist, AI engineer, or tech enthusiast, this course is designed to equip you to be able to deploy efficient AI systems. Note: This course was created by Janani Ravi. We are pleased to host this content in our library. Skills covered Large Language Model Operations (LLMOps), Generative AI, Kubernetes, Fine Tuning