Current
Intermediate
40% Off
AI Infrastructure and Cloud GPUs
Coursera · Coursera · Updated March 2026
Platform rating
4.5/5
AI Tutor Rating
8.3/10
Duration
6 weeks, 5 hours/week
Classes
42
Master the fundamentals of building and managing AI infrastructure using cloud-based GPU resources. Learn how to optimize computational performance, scale AI workloads, and implement efficient model training and deployment pipelines.
What you'll get
Configure and manage cloud GPU environments for AI projects
Optimize deep learning model training on distributed systems
Implement efficient data pipelines for large-scale AI workloads
Monitor and troubleshoot AI infrastructure performance
Cost-optimize cloud GPU resource utilization
Fit
Best for
Leaders
Analysts
Researchers
Decision-makers
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Programming experience, basic machine learning knowledge
Pricing
Free to audit, $49 for certificate
Certification
Certificate
Growth Leverage: Completing this course positions graduates for careers as AI Infrastructure Engineers, Cloud Solution Architects, or Machine Learning Operations (MLOps) specialists. It also prepares them for certifications like AWS Certified Machine Learning and Google Professional Data Engineer, enhancing their credentials in the rapidly evolving AI landscape.
Skills Value: The practical skills gained enable professionals to significantly improve the efficiency of AI deployments, which can lead to salary premiums of 20% or more in roles involving AI infrastructure management, given the high demand for expertise in cloud GPU optimization and model training efficiency.
cloud-computing
gpu-computing
infrastructure
deep-learning
machine-learning
distributed-systems