Luca Berton
mlops

Operationalizing ML Models: MLOps for Scalable AI

Luca Berton โ€ข
#mlops#machine learning#devops#ai infrastructure#luca berton

Operationalizing ML Models: MLOps for Scalable AI is your gateway to mastering the deployment and maintenance of machine learning systems in real-world environments. Created by the Starweaver Instructor Team and taught by Luca Berton, this Coursera course dives deep into the tools, workflows, and best practices required to build resilient AI infrastructure.

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๐Ÿง  What Youโ€™ll Learn


๐ŸŽ“ Who Should Take This Course?

This course is ideal for:

Prior experience with Python, ML basics, and Docker/containerization is recommended to get the most from this course.


๐Ÿ“š Course Overview

  • Introduction to MLOps and Operational Challenges
  • CI/CD Pipelines for Machine Learning
  • Monitoring and Observability in ML Deployments
  • Handling Drift, Failures, and Model Lifecycle
  • Scaling ML Systems Using Docker and Kubernetes
  • Real-World Case Studies from Netflix, Uber, and Google
  • Assignment: Deploying a Scalable ML Model with CI/CD
  • Final Thoughts and Continued Learning Path

๐Ÿงพ Certificate

Earn a Coursera shareable certificate to showcase your skills in scalable AI operations. Perfect for LinkedIn, resumes, or performance reviews.

Recently updated: March 2025 โ€“ Included with Coursera Plus.


๐Ÿงช Assignments & Discussions

  • Assignment: Deploy and Monitor a Machine Learning Model
  • Discussion: Lessons from Real-World MLOps Failures
  • Discussion: Tools You Use for Model Monitoring and Drift Detection

๐Ÿ‘จโ€๐Ÿซ About the Instructor

Luca Berton brings a practical approach to deploying ML systems. With expertise in DevOps, automation, and infrastructure management, Luca makes complex topics accessible to professionals of all levels.


Ready to turn your ML prototypes into production-ready systems?
Join now and operationalize your AI like the pros.

Enroll Now

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