Build end-to-end ML systems, optimize models, and deploy intelligent applications at scale
View CurriculumThis advanced course covers the full ML lifecycle from model development to production deployment. You'll master frameworks, MLOps practices, and real-world implementation patterns.
Build real ML pipelines and deploy models via Kubernetes and cloud services
Learn from ML architects with 15+ years in production systems development
Design and deploy an AI solution for a healthcare or fintech use case
Deep learning fundamentals, optimization techniques, and model evaluation
CI/CD pipelines, model registry, and infrastructure-as-code for ML systems
Scalable model serving, real-time inference, and A/B testing frameworks
Bias detection, explainable AI, and compliance frameworks
Engineered a scalable ML pipeline for medical imaging analysis with 98.7% accuracy in tumor detection
View Project →Built an anomaly detection system for banking transactions processing 1M+ events per second
View Study →Join 1,200+ graduates in production ML roles at top companies