Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Containerization Fundamentals in MLOps
- Assessing the specific requirements of the ML lifecycle
- Core Docker concepts applied to ML systems
- Best practices for ensuring environment reproducibility
Creating Containerized ML Training Pipelines
- Bundling model training code and its dependencies
- Setting up training jobs via Docker images
- Handling datasets and artifacts within containers
Containerizing Validation and Model Evaluation
- Recreating consistent evaluation environments
- Automating validation processes
- Recording metrics and logs from containerized instances
Containerized Inference and Serving Strategies
- Architecting inference microservices
- Tuning runtime containers for production efficiency
- Building scalable serving architectures
Orchestrating Pipelines with Docker Compose
- Managing multi-container ML workflows
- Handling environment isolation and configuration
- Integrating auxiliary services (such as tracking and storage)
ML Model Versioning and Lifecycle Oversight
- Monitoring models, images, and pipeline elements
- Maintaining version-controlled container environments
- Incorporating tools like MLflow or similar solutions
Deployment and Scaling of ML Workloads
- Executing pipelines in distributed settings
- Scaling microservices using native Docker capabilities
- Monitoring performance of containerized ML systems
Implementing CI/CD for MLOps with Docker
- Automating the build and deployment of ML components
- Validating pipelines in containerized staging environments
- 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 knowledge of containerization principles
Intended Audience
- MLOps Engineers
- DevOps Professionals
- 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
