Current
Intermediate
40% Off
Learn MLOps for Machine Learning
Coursera · Pearson · Updated March 2026
Platform rating
4.4/5
AI Tutor Rating
8.2/10
Duration
1-4 weeks
Classes
36
Learn MLOps including model deployment on AWS SageMaker, CI/CD pipelines, data management, and continuous monitoring.
What you'll get
Build end-to-end ML pipelines with CI/CD
Monitor model performance and detect drift
Deploy models on AWS SageMaker
Fit
Best for
Software Engineers
DevOps/MLOps Engineers
Data Engineers
Platform Engineers
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Basic ML knowledge
Pricing
Subscription
Certification
Certificate
Growth Leverage: Completing this course positions you for roles such as MLOps Engineer, Machine Learning Engineer, or Data Scientist, and equips you to pursue AWS Certified Machine Learning Specialty certification, opening doors to high-demand positions in AI-driven organizations.
Skills Value: The skills learned in this course enable you to effectively deploy and manage ML models, addressing critical business needs such as model performance optimization and drift detection, with salaries for MLOps roles often exceeding $120,000 annually, reflecting high market demand.
MLOps
AWS SageMaker
CI/CD
Monitoring
Data Management