LLM Metrics and Trade-Offs
Evaluate LLM skill through metrics like BLEU, ROUGE, F1, HELM, navigating accuracy, latency, cost, scalability trade-offs, addressing bias and ethical concerns.
Skill level
IntermediateTime to complete
Approx. 10 hoursCertificate of completion
Yes
About this skill path
The LLM Metrics and Trade-Offs learning journey equips AI practitioners, data scientists, and decision-makers with the skills to critically evaluate and select large language models for real-world applications. Across six concise courses, you’ll explore essential metrics like BLEU, ROUGE, F1, and HELM, and navigate key trade-offs in accuracy, latency, cost, and scalability. You’ll also address ethical concerns, including bias and fairness, and learn how to optimize model performance under operational constraints. By the end, you can confidently assess and select the right LLM based on technical, ethical, and business considerations.
Syllabus
Track 1: LLM Metrics and Trade-Offs
In this track, the focus will be on LLM key metrics, accuracy, performance, latency, scalability, cost efficiency, bias, fairness, ethical considerations, and selecting the right LLM.
course Large Language Models and Key Metricscourse LLM Accuracy, Performance, and Trade-Offscourse LLM Latency, Throughput, and Scalabilitycourse LLM Cost Efficiency, Model Size, and Resource Optimizationcourse LLM Bias, Fairness, and Ethical Considerationscourse Selecting the Right LLM
How it works
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