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Course Outline
Containerization Fundamentals for MLOps
- Analyzing ML lifecycle requirements
- Essential Docker concepts for ML systems
- Best practices for establishing reproducible environments
Constructing Containerized ML Training Pipelines
- Bundling model training code and its dependencies
- Setting up training jobs through Docker images
- Handling datasets and artifacts within containerized contexts
Containerizing Validation and Model Evaluation
- Recreating evaluation environments for consistency
- Streamlining validation workflows through automation
- Collecting metrics and logs from containerized processes
Containerized Inference and Serving
- Designing inference microservices
- Optimizing runtime containers for production performance
- Deploying scalable serving architectures
Orchestrating Pipelines with Docker Compose
- Managing multi-container ML workflow coordination
- Ensuring environment isolation and configuration control
- Incorporating auxiliary services such as tracking and storage
ML Model Versioning and Lifecycle Governance
- Monitoring models, images, and pipeline elements
- Implementing version-controlled container environments
- Integrating tools like MLflow or similar alternatives
Deploying and Scaling ML Workloads
- Executing pipelines across distributed environments
- Scaling microservices using native Docker strategies
- Observing and monitoring containerized ML systems
Implementing CI/CD for MLOps with Docker
- Automating the build and deployment phases for ML components
- Validating pipelines within containerized staging setups
- Safeguarding reproducibility and enabling rollback capabilities
Summary and Future Directions
Requirements
- Basic understanding of machine learning workflows
- Proficiency in Python for data or model development
- Familiarity with fundamental container concepts
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
