MLOps, LLMOps & AI Observability Training in USA

This course provides hands-on and conceptual understanding of deploying, managing, and monitoring machine learning (ML) and large language model (LLM) applications in production. Participants will learn about MLOps pipelines, LLMOps principles, and observability techniques to ensure reliability, traceability, and performance of AI systems.

Welcome to the official MLOps, LLMOps & AI Observability Training certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in USA. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

• Basic knowledge of machine learning concepts

• Familiarity with Python and Git

• Understanding of cloud or container-based deployment (Docker, Kubernetes optional)

• MLOps automation

• LLM deployment strategies

• ML pipeline monitoring and testing

• AI observability using tools like MLflow, WhyLabs, Arize, EvidentlyAI

• Model performance tracking, drift detection, and lineage tracing

By the end of this course, participants will be able to:

• Build, automate, and deploy ML pipelines using CI/CD

• Manage lifecycle and governance of LLM models

• Integrate AI observability tools for performance and drift monitoring

• Apply best practices for responsible and robust AI delivery