Course Outline
Foundations of Containerization in MLOps
- Examining requirements across the ML lifecycle
- Essential Docker concepts for ML systems
- Best practices for creating reproducible environments
Creating Containerized ML Training Pipelines
- Packaging model training code and dependencies
- Configuring training jobs via Docker images
- Managing datasets and artifacts within containers
Containerizing Validation and Model Evaluation
- Recreating consistent evaluation environments
- Automating validation workflows
- Capturing metrics and logs from containers
Containerized Inference and Serving
- Architecting inference microservices
- Optimizing runtime containers for production use
- Building scalable serving architectures
Pipeline Orchestration with Docker Compose
- Coordinating multi-container ML workflows
- Managing environment isolation and configuration
- Integrating auxiliary services (e.g., tracking, storage)
ML Model Versioning and Lifecycle Management
- Tracking models, images, and pipeline components
- Maintaining version-controlled container environments
- Integrating tools such as MLflow or similar solutions
Deploying and Scaling ML Workloads
- Executing pipelines in distributed environments
- Scaling microservices using Docker-native methods
- Monitoring containerized ML systems
CI/CD for MLOps with Docker
- Automating the build and deployment of ML components
- Testing pipelines in containerized staging environments
- Guaranteeing reproducibility and rollback capabilities
Conclusion and Future Steps
Requirements
- A solid grasp of machine learning workflows
- Proficiency in Python for data or model development
- Basic knowledge of container fundamentals
Target Audience
- MLOps engineers
- DevOps practitioners
- Data platform teams
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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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
