MLOps

The MLOps Specialization | Machine Learning Operations is a comprehensive, career-oriented program designed to help learners move from experimental machine learning to production-grade ML systems.

You will gain hands-on MLOps skills using Python, Rust, GitHub Copilot, SageMaker, Azure ML, MLflow, and Hugging Face to build, deploy, and manage real-world AI solutions.

Hands-On Learning & Applied Projects

Throughout the specialization, learners work on practical, real-world MLOps projects, supported by GitHub repositories and live mentoring.

You will:

• Automate data preprocessing and feature engineering with Python
• Develop a real ML/AI solution using pair programming and GitHub Copilot
• Build web applications and CLI tools using Gradio, Hugging Face, and Click
• Implement GPU-accelerated ML tasks using Rust
• Train, optimize, and deploy ML models on Amazon SageMaker and Azure ML
• Design a complete MLOps pipeline with MLflow
• Fine-tune and deploy LLMs and ONNX-based models
• Create interactive demos to showcase production-ready ML solutions

Program Structure (Blended Learning Format)

Online Learning – Duke University

The online component, developed by Duke University, consists of 4 in-depth courses covering the theoretical foundations and practical tools of MLOps.

🔹 Course 1 – Python Essentials for MLOps

You develop clean, testable, and production-ready Python code, not just experimental scripts or notebooks.

🔹 Course 2 – DevOps, DataOps, and MLOps Pipelines

You gain hands-on experience with how ML systems are deployed and managed in real-world enterprise environments.

🔹 Course 3 – Data Science, Cloud ML, and Production Deployment

You learn to combine data science and cloud technologies to deliver scalable ML solutions.

🔹 Course 4 – Advanced MLOps with MLflow and Hugging Face

You gain practical experience deploying modern ML models and large language models (LLMs) in production environments.

• Instructors (MUST University): Our faculty from MUST University are academic leaders and experts in MLOps, bringing a blend of theoretical knowledge and real-world application to the curriculum.
• Instructors (Duke University): The program also features top instructors from Duke University, renowned for their advanced research and practical expertise in MLOps, covering key concepts and industry best practices.