Hands-On MLOps Fundamentals for ML Engineers

Coursera MOOC / Non-credit USD 49
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Hands-On MLOps Fundamentals for ML Engineers

About this course

Transition seamlessly from DevOps to MLOps and master the complete machine learning lifecycle—from data ingestion to production deployment. This hands-on Specialization equips ML engineers with critical skills in data engineering, model deployment, monitoring, and governance to build reliable, scalable ML systems. Through real-world projects culminating in an automated insurance claim processing application, you'll gain job-ready expertise in MLOps tools and best practices aligned with 2026's fastest-growing technical skills. Join thousands of professionals mastering the critical intersection of machine learning and operations. Enrol in the Hands-On MLOps Fundamentals for ML Engineers Specialization today and position yourself at the forefront of one of tech's fastest-growing fields.

What you'll learn

  • understand the machine learning lifecycle
  • perform data ingestion
  • deploy ML models in production
  • monitor ML systems
  • implement governance frameworks for ML projects

Course objectives

  • to develop a strong foundation in MLOps practices
  • to gain practical experience through real-world projects
  • to advance your career in one of tech's fastest-growing fields

Skills you'll gain

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