DevOps, DataOps, MLOps

AI pair programming meets operations

This advanced Coursera course applies MLOps to real problems and leans on GitHub Copilot as a coding partner while building machine learning and AI applications. Its premise is that the habits that make software reliable also apply to data and model work.

Technologies on the map

The skill list spans containerization, serverless computing, web frameworks, Hugging Face models and the Rust language, so the course covers a broad range of tooling. Expect to switch between application code, deployment configuration and model artifacts.

Who it is for

• Data scientists, software engineers and developers who ship ML features.
• Analysts working with ML tools who want to understand how those tools reach production.
• People already comfortable with DevOps who want the ML side explained.

Treat it as a survey of end-to-end delivery, and plan to go deeper on the parts that matter to your own stack.