LLMOps Course in Hyderabad

Deploy, evaluate and monitor large language model applications in production

The LLMOps course teaches you to take LLM applications from prototype to dependable production service. You start with the LLM application lifecycle and how it differs from classical MLOps, then learn prompt and configuration management, versioning and registries, building evaluation datasets and automatic and human evaluation, and regression testing of prompts, models and retrieval pipelines. You instrument applications with tracing and logging using tools such as MLflow 3's GenAI features, LangSmith or Langfuse, monitor quality, latency, token cost and safety in production, and add guardrails against prompt injection, data leaks and unsafe output. Deployment modules cover serving hosted and open models, including self-hosting with vLLM, caching, batching, routing between models, rate limits, CI/CD pipelines with GitHub Actions, containers and Kubernetes at an overview level, and cost optimisation. The course suits developers, data scientists and DevOps professionals with intermediate Python who have built a basic LLM or RAG application. Labs use a running RAG application as the case study. Classes run in Ameerpet, Hyderabad, and in live online batches.