LLMOps Concepts

This course will provide the conceptual and practical skills necessary for taking your LLM application from idea to deployment and maintenance. You'll be taught the different phases of the LLMOps lifecycle, along with the challenges and considerations within each. You'll gain a solid understanding of the technical and operational aspects of building a reliable, efficient, and secure LLM application.

Learning about the concepts within LLMOps would benefit anyone interested in leveraging or integrating AI solutions with LLM applications into their organization or personal project.

LLMOps focuses on managing large-scale language models that primarily generate text, using prompt engineering and fine-tuning techniques. In contrast, MLOps handles smaller models applicable to various data types, involving feature engineering and model selection. LLMs are more unpredictable and can produce incorrect information, while traditional ML models are generally more predictable and produce task-specific outputs like labels or probabilities.