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Course Outline
Core Concepts of Containerization in MLOps
- Analyzing ML lifecycle requirements
- Essential Docker concepts for ML systems
- Best practices for creating reproducible environments
Creating Containerized ML Training Pipelines
- Bundling model training code with necessary dependencies
- Setting up training jobs via Docker images
- Handling datasets and artifacts within containers
Containerizing Validation and Model Assessment
- Duplicating evaluation environments for consistency
- Streamlining validation workflows through automation
- Recording metrics and logs from container instances
Containerized Inference and Model Serving
- Structuring inference microservices
- Tuning runtime containers for production performance
- Building scalable serving architectures
Orchestrating Pipelines with Docker Compose
- Managing multi-container ML workflows
- Handling environment isolation and configuration management
- Connecting auxiliary services (e.g., tracking systems, storage)
ML Model Versioning and Lifecycle Governance
- Monitoring models, images, and pipeline components
- Managing version-controlled container environments
- Integrating with tools like MLflow or similar platforms
Deploying and Scaling ML Workloads
- Executing pipelines in distributed settings
- Scaling microservices using native Docker methods
- Observing and monitoring containerized ML systems
Implementing CI/CD for MLOps using Docker
- Automating the build and deployment of ML components
- Validating pipelines in containerized staging environments
- Guaranteeing reproducibility and rollback capabilities
Conclusions and Future Directions
Requirements
- Proficiency in machine learning workflows
- Hands-on experience with Python for data processing or model development
- Basic knowledge of containerization fundamentals
Target Audience
- MLOps engineers
- DevOps practitioners
- Data platform teams
21 Hours
Testimonials (3)
How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation
the trainer had a lot of knowledge and patience to share with us
Bogdan Olaru
Course - Introduction to Docker
The knowledge and exchanges with Augustin
