MLOps and LLMOps

STARTS SOON ON MONDAY, FEBRUARY 3, 2025!

Unlock the power of operationalizing AI systems with our comprehensive MLOps and LLMOps course, designed for engineers and practitioners. Start with the principles of continuous integration, deployment (CI/CD), and version control tailored for machine learning workflows. Learn to automate data pipelines, model training, and monitoring using tools like MLflow, DVC, and Airflow.

Gain expertise in serving and scaling large language models (LLMs) with techniques like sharding, quantization, and optimization. Explore infrastructure orchestration with Kubernetes and cloud platforms for deploying AI at scale. Delve into advanced observability, including drift detection, explainability, and model retraining triggers.

Discover best practices for handling multi-modal pipelines and hybrid systems, integrating LLMs into retrieval-augmented architectures and streaming applications. Address ethical and regulatory considerations, ensuring compliance in real-world deployments.

By the end of this course, you’ll be equipped to design, deploy, and manage robust MLOps and LLMOps pipelines, unlocking scalability, efficiency, and reliability for AI systems at any scale.