Machine Learning Operations

Unlike typical ML courses that focus primarily on model building, this program emphasizes the operational aspects of putting models into production. It covers the complete MLOps lifecycle across multiple platforms (AWS, Azure) and tools (MLflow, Hugging Face), preparing you for real-world implementation challenges.

The program includes specific coverage of fine-tuning and deploying Large Language Models using Hugging Face, reflecting the growing importance of these models in production environments. This includes containerization strategies using the ONNX format for efficient deployment.

The program is taught by experts from Pragmatic AI Labs, including Noah Gift (Founder and Executive in Residence) and Alfredo Deza (Adjunct Assistant Professor in the Pratt School of Engineering), who bring practical industry experience to the curriculum.

The program provides hands-on experience with both Amazon SageMaker (AWS) and Azure ML (Microsoft), giving you versatile skills applicable across the two leading cloud providers for machine learning operations.

You'll gain expertise with MLflow for experiment tracking and model management, Hugging Face for working with transformer models, containerization technologies, and cloud-specific MLOps services from AWS and Azure. The program emphasizes practical implementation rather than just theoretical concepts.