This course is designed to help aspiring data scientists, ML engineers, and developers master Docker for building and deploying machine learning applications. You’ll start with the fundamentals of Docker, then move on to containerizing ML workflows, managing environments, and working with Docker volumes. You’ll also learn advanced concepts like multi-stage builds and Docker Compose for handling complex applications. Finally, the course guides you through deploying ML apps on AWS and debugging Docker containers effectively.

By the end of this course, you will be able to:

• Understand Docker basics and how containers work
• Package and run machine learning applications in Docker
• Manage environment variables and persistent storage using volumes
• Optimize builds with caching and multi-stage workflows
• Use Docker Compose to orchestrate multi-container setups
• Deploy ML applications seamlessly on AWS
• Debug and troubleshoot Docker containers with confidence

This course blends theory with hands-on examples, giving you the practical skills needed to take your ML projects from local development to scalable cloud deployments.

What is the refund policy for this course?
You can request a refund within 4 days of enrollment and as long as you have completed less than 40% of the content.

Course Duration - 7 Hrs

Queries: support@campusx.in