Amazon SageMaker - ML platform
The training focuses on the practical use of the Amazon SageMaker platform in machine learning projects. Participants will learn the full lifecycle of an ML model - from data preparation, to training, to production deployment. The program combines workshop sessions with theoretical lectures, providing a balanced approach to learning. Classes are conducted in an interactive format, with an emphasis on practical exercises on real use cases.
Issues
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Amazon SageMaker architecture and components
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Integration with the AWS ecosystem
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Data processing and preparation
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Machine learning algorithms
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Distributed Training
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ML process automation
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Implementing models
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Monitoring and maintenance
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Cost optimization
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Safety and compliance
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MLOps best practices
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Scaling up ML solutions
Benefits
- The participant will be able to independently prepare the SageMaker environment for ML projects
- The ability to effectively manage the lifecycle of models from experimentation to production deployment
- Will learn to optimize infrastructure costs through proper resource management
- Best practices for monitoring and maintaining ML models in production
- Will be able to design scalable ML solutions leveraging AWS cloud capabilities
- Will develop the ability to integrate SageMaker with other AWS services
- Will gain a working knowledge of ML/AI process automation
- Will gain the ability to diagnose and resolve problems in ML projects
Who is this training for?
Prerequisites
- Basic knowledge of Python and data analysis libraries
- Experience working with machine learning models
- Knowledge of basic AWS cloud concepts
- Ability to work with Linux/Unix systems
Training program
Platform architecture and components
- Preparation of the development environment
- Integration with AWS services
- Management of computing instances
- Data processing and preparation
- Working with Amazon S3 as a data source
- Data Transformation in Processing Jobs
Feature Engineering
- Creating data processing pipelines
Training models
- SageMaker's built-in algorithms
Adjusting hyperparameters
- Distributed Training
- Monitoring the training process
- Model implementation and management
- Endpoints and deployment configuration
Automatic scaling
- A/B Testing of models
- Performance monitoring and updates
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 Amazon SageMaker - ML platform training for?
This training is designed for professionals looking to develop skills in amazon sagemaker - ml platform. Required level: intermediate.
How long is the Amazon SageMaker - ML platform training?
The training lasts 3. 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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Interested in this training?
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