MLOps & Production ML Systems
Master end-to-end ML system design with comprehensive coverage of model versioning, CI/CD pipelines, monitoring, scalability, Docker, Kubernetes, and MLflow with direct industry mentorship.
Production-Ready MLOps Mastery
Our 20-week MLOps & Production ML Systems program is the most comprehensive course in Sri Lanka for building, deploying, and maintaining machine learning systems at enterprise scale. This premium program bridges the gap between ML development and production deployment.
You'll work directly with senior ML engineers from leading Sri Lankan fintech and e-commerce companies including Pickme, LSEG Technology, and hSenid Mobile. The course covers advanced topics like distributed training, A/B testing for ML, feature stores, and real-time inference systems.
Premium Features
- Direct industry mentorship program
- Docker & Kubernetes mastery
- Production monitoring & alerting
- Advanced CI/CD for ML pipelines
- Feature stores & data versioning
Enterprise-Level Career Impact
Leadership Career Trajectories
Senior ML Engineer → Head of ML Platform at Pickme
Salary: 280,000 → 650,000 LKR/month
DevOps Engineer → Principal MLOps Engineer at LSEG
Salary: 200,000 → 550,000 LKR/month
Founded ML consulting firm serving US clients
Revenue: 1.2M+ LKR/month
High-Demand Specializations
Global Opportunities
MLOps specialists are in extremely high demand globally. Our graduates secure remote positions with international companies and consulting contracts.
Enterprise-Grade Technology Stack
Containerization
- Docker containerization mastery
- Multi-stage Docker builds
- Container security best practices
- Container registry management
Kubernetes
- K8s cluster management
- Helm charts for ML deployments
- Auto-scaling ML workloads
- Service mesh for ML services
CI/CD for ML
- Jenkins & GitHub Actions
- Automated model testing
- Progressive deployment strategies
- Rollback & canary deployments
Monitoring & Observability
- Prometheus & Grafana setup
- Model drift detection
- Performance monitoring
- Alerting & incident response
MLflow & Experiment Tracking
- MLflow deployment & scaling
- Model registry management
- Experiment tracking at scale
- Model versioning strategies
Cloud Platforms
- AWS SageMaker production
- Google Cloud AI Platform
- Azure ML deployment
- Multi-cloud strategies
Advanced Production Patterns
Feature Engineering at Scale
Build robust feature stores and data pipelines that can handle millions of predictions per day. Learn advanced techniques for feature engineering, validation, and serving.
- • Feast feature store implementation
- • Real-time and batch feature serving
- • Feature validation and monitoring
- • Data lineage and governance
A/B Testing for ML
Design and implement sophisticated A/B testing frameworks for machine learning models. Learn statistical methods for measuring model performance improvements.
- • Multi-armed bandit implementations
- • Statistical significance testing
- • Model champion/challenger frameworks
- • Business impact measurement
Enterprise Security & Governance
Production Security Standards
Enterprise ML systems require military-grade security protocols. Students learn comprehensive security practices including secure model serving, data encryption, access controls, and compliance frameworks essential for regulated industries.
Zero-Trust ML Architecture
Identity-based access control and encrypted model serving
Data Privacy & Encryption
End-to-end encryption and differential privacy techniques
Access Control & Auditing
Role-based permissions and comprehensive audit trails
Compliance & Governance
Navigate complex regulatory environments with comprehensive governance frameworks. Learn to build ML systems that meet SOX, GDPR, HIPAA, and other critical compliance requirements.
Regulatory Compliance
SOX, GDPR, HIPAA compliance for ML systems
Model Governance
Approval workflows and change management processes
Risk Management
Model risk assessment and mitigation strategies
Enterprise Compliance Framework
SOX Compliance
Financial reporting standards
GDPR
European data protection
HIPAA
Healthcare data privacy
ISO 27001
Information security
Built for Industry Leaders
Senior ML Engineers
Experienced ML practitioners ready to transition into MLOps leadership roles, building production-grade ML infrastructure for enterprise-scale applications.
DevOps Engineers
Senior DevOps professionals looking to specialize in ML infrastructure, bringing traditional DevOps practices to machine learning model deployment and operations.
Platform Architects
Technical architects designing enterprise ML platforms and infrastructure. Ideal for those building ML capabilities across large organizations.
Engineering Managers
Technical leaders managing ML teams who need deep understanding of production ML systems to make strategic technology and staffing decisions.
Technical Founders
Startup founders building AI-first companies who need hands-on expertise in scalable ML infrastructure to guide their technical strategy and architecture decisions.
Consultants
Independent consultants and solutions architects helping enterprises implement ML at scale. Perfect for building a specialized MLOps consulting practice.
Executive Prerequisites
Required Leadership Experience
- • 5+ years in senior technical roles
- • Experience with distributed systems
- • Cloud platform expertise (AWS/GCP/Azure)
- • Strong understanding of DevOps practices
- • Experience managing technical teams
Strategic Technical Skills
- • Enterprise architecture experience
- • Budget and resource management
- • Vendor evaluation and procurement
- • Risk assessment and mitigation
- • Stakeholder communication skills
Executive-Level Assessment & Certification
Strategic Project Assessment
Leadership Milestones
Executive Performance Dashboard
Track your strategic progress with executive-level metrics including business impact, technical leadership, and organizational transformation capabilities.
Executive MLOps Certification
Earn the most prestigious MLOps certification in South Asia, demonstrating executive-level expertise in production ML systems and strategic technology leadership.
Executive Capstone Portfolio
Enterprise Architecture
Design and implement enterprise-grade ML platform architecture for Fortune 500 scale
Business Impact Analysis
Quantify ROI and business impact of MLOps initiatives with comprehensive metrics
Team Leadership Plan
Develop organizational change management and team scaling strategies
Ready to Lead ML at Scale?
Join our exclusive MLOps & Production ML Systems program starting January 15, 2025. Only 15 seats available for this executive-level certification program.
Build Your Foundation First
ML Engineering Foundations
Build strong fundamentals with our 16-week comprehensive program covering supervised learning, feature engineering, and deployment pipelines using scikit-learn and TensorFlow.
Deep Learning & Neural Networks
Advanced 12-week specialization in deep neural networks, CNNs, RNNs, transformers, PyTorch mastery, and cutting-edge research in artificial intelligence.