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Duke University

DevOps, DataOps, MLOps

Learn how to apply Machine Learning Operations (MLOps) to solve real-world problems. The course covers end-to-end solutions with Artificial Intelligence (AI) pair programming using technologies like GitHub Copilot to build solutions for machine learning (ML) and AI applications. This course is for people working (or seeking to work) as data scientists, software engineers or developers, data analysts, or other roles that use ML. By the end of the course, you will be able to use web frameworks (e.g., Gradio and Hugging Face) for ML solutions, build a command-line tool using the Click framework, and leverage Rust for GPU-accelerated ML tasks. Week 1: Explore MLOps technologies and pre-trained models to solve problems for customers. Week 2: Apply ML and AI in practice through optimization, heuristics, and simulations. Week 3: Develop operations pipelines, including DevOps, DataOps, and MLOps, with Github. Week 4: Build containers for ML and package solutions in a uniformed manner to enable deployment in Cloud systems that accept containers. Week 5: Switch from Python to Rust to build solutions for Kubernetes, Docker, Serverless, Data Engineering, Data Science, and MLOps.

Status: PyTorch (Machine Learning Library)
Status: Responsible AI
AdvancedCourse45 hours

Featured reviews

RV

5.0Reviewed Jun 23, 2024

Extremely usefull to understand concepts of MLOps, containers, CI/CD

RR

5.0Reviewed Jun 24, 2024

Very well explained and great step by step examples

SM

4.0Reviewed Dec 22, 2025

A slightly shorter duration could have been better.

ND

5.0Reviewed Aug 21, 2024

Great learning resources, concise presentations, and clear explanations of all topics

All reviews

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