Build scalable AI infrastructure. GPU clusters, LLM deployments, and high-performance AI workloads.
From traditional DevOps to AI infrastructure specialist in 14 weeks
Comprehensive curriculum designed by AI infrastructure and DevOps experts
Build production-grade infrastructure that powers enterprise AI applications
Build a complete GPU cluster management system with auto-scaling, job scheduling, and resource optimization for distributed AI training.
Design and implement end-to-end MLOps infrastructure with automated training, testing, and deployment of machine learning models.
Build scalable infrastructure for serving large language models with auto-scaling, load balancing, and cost optimization.
Create a multi-cloud AI platform that can provision GPU resources across AWS, GCP, and Azure based on workload requirements and cost optimization.
Build high-performance data pipelines for AI training with real-time data ingestion, transformation, and feature stores.
Design infrastructure for deploying AI models at the edge with automated model optimization, OTA updates, and monitoring.
Implement comprehensive monitoring for AI infrastructure including GPU utilization, model performance, and cost tracking with automated alerting.
Flexible pricing options to fit your learning style and budget
Complete course access
With live sessions & 1-on-1 guidance
Complete career transformation package
Join the next generation of engineers building the infrastructure that powers the AI revolution