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Duration 21 hours
Course Outline
Foundations of Containerization for MLOps
- Recognizing ML lifecycle requirements
- Essential Docker concepts for ML systems
- Best practices for ensuring reproducible environments
Creating Containerized ML Training Pipelines
- Bundling model training code and its dependencies
- Setting up training jobs using Docker images
- Handling datasets and artifacts within containers
Containerizing Validation and Model Evaluation
- Recreating evaluation environments consistently
- Automating validation processes
- Collecting metrics and logs from containers
Containerized Inference and Serving
- Architecting inference microservices
- Tuning runtime containers for production use
- Establishing scalable serving architectures
Orchestrating Pipelines with Docker Compose
- Managing multi-container ML workflows
- Handling environment isolation and configuration
- Integrating auxiliary services (e.g., tracking, storage)
ML Model Versioning and Lifecycle Management
- Monitoring models, images, and pipeline components
- Maintaining version-controlled container environments
- Incorporating MLflow or comparable tools
Deploying and Scaling ML Workloads
- Executing pipelines in distributed settings
- Expanding microservices via Docker-native methods
- Observing containerized ML systems
Implementing CI/CD for MLOps with Docker
- Automating the build and deployment of ML components
- Testing pipelines in containerized staging areas
- Guaranteeing reproducibility and rollback capabilities
Conclusion and Future Directions
Requirements
- A solid grasp of machine learning workflows
- Practical experience with Python for data or model development
- Basic familiarity with container fundamentals
Target Audience
- MLOps engineers
- DevOps practitioners
- Data platform teams
Testimonials (2)
As i said before , for a person like me (no exp. ) this was a gateway to understanding features and functions with these programs/tools & etc. .
Patrick V. Duylovski - UBB + DZI (KBC GROUP)
Course - Docker and Kubernetes
multi-tiered, structured course programme.
