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Course Outline
Containerization Foundations for MLOps
- Analyzing requirements across the ML lifecycle
- Essential Docker concepts relevant to ML systems
- Best practices for establishing reproducible environments
Constructing Containerized ML Training Pipelines
- Packaging model training code and associated dependencies
- Setting up training jobs via Docker images
- Managing datasets and artifacts within containers
Containerizing Validation and Model Evaluation
- Recreating evaluation environments consistently
- Automating validation processes
- Capturing metrics and logs from containerized instances
Containerized Inference and Serving
- Architecting inference microservices
- Optimizing runtime containers for production workloads
- Implementing scalable serving architectures
Orchestrating Pipelines with Docker Compose
- Coordinating complex, multi-container ML workflows
- Managing environment isolation and configuration
- Integrating auxiliary services such as tracking and storage
ML Model Versioning and Lifecycle Management
- Tracking models, images, and pipeline components
- Maintaining version-controlled container environments
- Integrating tools like MLflow for lifecycle management
Deploying and Scaling ML Workloads
- Executing pipelines in distributed settings
- Scaling microservices using native Docker capabilities
- Monitoring the health and performance of containerized ML systems
Implementing CI/CD for MLOps with Docker
- Automating the build and deployment of ML components
- Testing pipelines in containerized staging environments
- Safeguarding reproducibility and enabling seamless rollbacks
Summary and Future Directions
Requirements
- Foundational knowledge of machine learning workflows
- Practical experience with Python for data or model development
- Basic familiarity with containerization 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
