Current
Intermediate
40% Off
AI Agents and MLOps for Production-Ready AI
Coursera · Packt · Updated March 2026
Platform rating
4.4/5
AI Tutor Rating
8.2/10
Duration
1-4 weeks
Classes
36
Learn AI agents and MLOps for production including LangGraph, CrewAI, Docker, Kubernetes, and cloud deployment on AWS/GCP/Azure.
What you'll get
Deploy models to production with Docker and Kubernetes
Scale ML systems for high-throughput inference
Build AI agent systems for production
Fit
Best for
Software Engineers
DevOps/MLOps Engineers
Data Engineers
Platform Engineers
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Python, basic ML
Pricing
Subscription
Certification
Certificate
Growth Leverage: Completing this course opens pathways to roles such as MLOps Engineer, AI Systems Architect, and Data Engineer, empowering professionals to pursue certifications like the Google Professional Machine Learning Engineer and leading to opportunities with top tech companies utilizing AI in production settings.
Skills Value: The skills gained enable deployment and scaling of AI systems using Docker and Kubernetes, addressing high-demand challenges in cloud environments, with MLOps professionals earning salaries that can exceed $120,000 annually due to the critical need for efficient AI model management.
MLOps
AI Agents
Docker
Kubernetes
LangGraph
CrewAI