GenAI Model Development and Production Engineering
Master advanced fine-tuning, scalable deployments, and AI system maintenance. Build production-ready GenAI models and infrastructure that deliver real-world enterprise value.
Overview
This course includes:
- On-demand videos
- Practice assessments
- Multiple hands-on learning activities
- Exposure to a real-world project
- 100% self-paced learning opportunities
- Certification of completion
Frustrated with generic AI models that don't understand your specific domain or business needs? Most organizations struggle to move beyond demo-level AI implementations to robust, scalable systems that deliver consistent value in production environments.
This course transforms you into a complete GenAI production engineer who can fine-tune foundation models for specialized applications, architect enterprise-grade deployment infrastructure, and maintain AI systems that scale reliably under real-world demands. You'll master advanced fine-tuning techniques for domain-specific customization, implement comprehensive monitoring and maintenance frameworks, and deploy production-ready systems with proper safety guardrails and performance optimization.
By the end of this course, you'll confidently execute the complete AI production lifecycle - from custom model development to bulletproof deployment pipelines, automated maintenance protocols, and scalable infrastructure that handles enterprise workloads. You'll have the expertise to build AI systems that actually work in production, not just in demos.
Join the exclusive group of engineers building and maintaining the mission-critical AI systems that power tomorrow's most innovative companies and become the production specialist every organization desperately needs.
Skills You Will Gain
Learning Outcomes (At The End Of This Program, You Will Be Able To...)
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Execute fine-tuning workflows for custom model development with evaluation frameworks.
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Implement production deployment strategies with infrastructure planning and monitoring systems.
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Construct comprehensive maintenance protocols with automated scheduling and performance tracking.
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Apply advanced deployment patterns for diverse GenAI applications with scalability considerations.
Prerequisites
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Advanced Python programming and ML frameworks.
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Experience with cloud platforms and containerization.
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Understanding of model training and evaluation.
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Knowledge of production system architecture.
Who Should Attend
- ML Engineers specializing in production systems
- DevOps Engineers handling AI deployments
- Platform Engineers building AI infrastructure
- Technical Architects designing scalable AI systems
