MLOps: CI/CD for machine learning
Advanced training dedicated to implementing full cycle CI/CD in machine learning projects. The program integrates DevOps best practices with ML project requirements, providing participants with an in-depth understanding of automating ML processes from development to production deployment. The training uses hands-on workshops and real-world scenarios, allowing participants to gain experience in building scalable and reliable ML pipelines.
Issues
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MLOps architecture
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CI/CD Pipelines
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Machine learning automation
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Continuous Training
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Continuous Deployment
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Monitoring of models
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ML infrastructure
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Containerization
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Orchestration
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ML security
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Scalability of systems
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Incident management
Benefits
- The participant will develop advanced skills in the design and implementation of complex CI/CD solutions for machine learning projects
- Will gain in-depth knowledge of automating the entire lifecycle of ML models, from development to production deployment
- Will learn to build scalable and reliable ML pipelines in line with DevOps best practices
- Will develop the ability to effectively manage infrastructure and resources in ML projects
- Will learn advanced techniques for monitoring and optimizing the performance of ML systems
- Will gain hands-on experience in implementing security and compliance in ML pipelines
Who is this training for?
Prerequisites
- Advanced knowledge of DevOps practices
- Experience in ML projects
- Knowledge of version control systems
- Python programming basics
Training program
MLOps systems architecture
- CI/CD pipeline design for ML
- Integration with version control systems
- Management of ML environments
ML process automation
- Automatic training of models
- Testing and validation of models
- Continuous Training (CT)
- Training data management
- Implementation and monitoring
- Strategies for implementing models
- Continuous Deployment (CD)
Performance monitoring
- Incident management
- Infrastructure and scalability
- Microservices architecture for ML
- Containerization of ML models
- Orchestration of containers
Resource management
- Safety and compliance
ML pipeline security
- Audit and compliance
Access management
- Data and model protection
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
What are the prerequisites for this training?
For MLOps: CI/CD for machine learning we recommend: Advanced knowledge of DevOps practices; Experience in ML projects; Knowledge of version control systems.
What is the format and duration of this training?
The training lasts 5 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.
Who is this training designed for?
This training is designed for: DevOps engineers specializing in ML; ML/AI solution architects; Data Scientists interested in automation.
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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?
Contact us - we'll prepare an offer tailored to your organization's needs.