Mastering LLM Evaluation: Build Reliable Scalable AI Systems

Partner: Udemy
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Description: Unlock the power of LLM evaluation and build AI applications that are not only intelligent—but also reliable, efficient, and cost-effective. This comprehensive course teaches you how to evaluate large language model outputs across the entire development lifecycle—from prototype to production. Whether you're an AI engineer, product manager, or ML ops specialist, this program gives you the tools to drive real impact with LLM-driven systems.Modern LLM applications are powerful, but they're also prone to hallucinations, inconsistencies, and unexpected behavior. That’s why evaluation is not a nice-to-have—it's the backbone of any scalable AI product. In this hands-on course, you'll learn how to design, implement, and operationalize robust evaluation frameworks for LLMs. We’ll walk you through common failure modes, annotation strategies, synthetic data generation, and how to create automated evaluation pipelines. You’ll also master error analysis, observability instrumentation, and cost optimization through smart routing and monitoring.What sets this course apart is its focus on practical labs, real-world tools, and enterprise-ready templates. You won’t just learn the theory of evaluation—you’ll build test suites for RAG systems, multi-modal agents, and multi-step LLM pipelines. You’ll explore how to monitor models in production using CI/CD gates, A/B testing, and safety guardrails. You’ll also implement human-in-the-loop (HITL) evaluation and continuous feedback loops that keep your system learning and improving over time.You’ll gain skills in annotation taxonomy, inter-annotator agreement, and how to build collaborative evaluation workflows across teams. We’ll even show you how to tie evaluati
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Price: 99.99
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Source: Impact
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