Kubeflow on AWS - machine learning in the cloud
Advanced training on implementing and managing machine learning solutions in an AWS environment using the Kubeflow platform. The training program combines practical aspects of ML task orchestration with advanced techniques for deploying models in a production environment. Through an intensive workshop, participants will learn the full lifecycle of an ML project, from data preparation to model training to deployment and monitoring in production. The training uses real-world use cases and MLOps best practices, providing a comprehensive understanding of the manufacturing process in machine learning projects.
Issues
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Kubeflow Architecture
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ML experiment management
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Distributed model training
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Data processing pipelines
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Model versioning
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Performance monitoring
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Serving predictions
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Optimization of resources
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ML process automation
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Scaling up solutions
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Environmental management
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MLOps best practices
Benefits
- The training will develop practical skills for implementing ML projects in an AWS production environment
- Upon completion of the course, efficiency in managing the lifecycle of machine learning models will increase
- The experience gained will enable the implementation of efficient and scalable MLOps solutions
- Practical knowledge will enable optimization of ML model training and deployment processes
- The acquired skills will accelerate the organization's transformation towards mature ML practices
- Of the Kubeflow platform will increase efficiency in automating ML processes
Who is this training for?
Prerequisites
- Basic knowledge of machine learning
- Experience with Kubernetes
- Knowledge of AWS basics
- Python programming skills
Training program
Solution architecture
- Configuring the environment
- Integration with AWS services
- Management of computing resources
- Data processing and experimentation
- Data processing pipelines
- Experiment management
Tracking models
- Data and code versioning
- Model training and optimization
Scattered training
- Hyperparameter tuning
- GPU resource management
- Performance monitoring
- Implementation and monitoring
- Model deployment strategies
Serving predictions
- Performance monitoring
- Model version management
Delivery Methods
Online
- Convenience of participating from anywhere
- Interactive live sessions with trainer
- Materials available for 30 days
- No travel costs
On-site
- Direct contact with trainer and group
- Intensive hands-on workshops
- Networking with other participants
- Full focus on learning
Frequently asked questions
Who is the Kubeflow on AWS - machine learning in the cloud training for?
This training is designed for professionals looking to develop skills in kubeflow on aws - machine learning in the cloud. Required level: advanced.
How long is the Kubeflow on AWS - machine learning in the cloud training?
The training lasts 4. Available in online or on-site format.
Will I receive a certificate?
Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.
Can this training be conducted for a closed group?
Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.
Request a quote
Funding Options
Check funding options for your company
Development Services Database
Up to 80% funding for SMEs from EU funds
Check availabilityNational Training Fund
Up to 100% funding for employers
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We train teams at Poland's largest companies
Interested in this training?
Contact us - we'll prepare an offer tailored to your organization's needs.