Machine Learning Engineer
Blend engineering rigor with ML expertise to build, deploy and run models responsibly in real products.
Accelerated Delivery
Operationalise ML to cut project timelines significantly.
Measurable ROI
Drive new revenue and cost savings through applied ML.
Operational Safety
Robust monitoring, security and governance for ML at scale.
Key skills you will gain
Curriculum
A modular, guided experience that pairs flexible learning with practical projects.
ML Lifecycle, Metrics & Experiment Design
From framing to evaluation and iteration.
Advanced Python & Software Engineering
Production-grade code, testing and packaging.
Data for ML: Feature Engineering & Quality
Build performant datasets and features.
Classical Machine Learning Methods
Regression, trees, ensembles and more.
Deep Learning & Foundation Models
Modern architectures for CV/NLP/sequence tasks.
MLOps & ML Pipelines
Automation, reproducibility and CI/CD for ML.
Deployment, Monitoring & Reliability
Serving models and operating them safely.
Responsible AI, Security & Governance
Risk, ethics and compliance in production.
The ML Engineer in the Workplace
Stakeholders, delivery and ROI.
Ready to start your journey?
Book a discovery call to learn how this course can accelerate your career while delivering value to your employer.