Data Science & MLAdvanced
MLOps — Deploying Models to Production
Bridges the gap between data science and engineering. Learn MLflow, model serving, containerisation with Docker, CI/CD for ML, and monitoring model drift.
Tools & Technologies
PythonMLflowDockerFastAPIGitHub Actions
Course Curriculum
1
ML Lifecycle
- Experiment tracking with MLflow
- Model registry
- Versioning
2
Model Serving
- REST APIs with FastAPI
- Batch vs real-time inference
- Docker containerisation
3
CI/CD for ML
- Automated testing
- GitHub Actions pipelines
- Model validation
4
Monitoring
- Data drift detection
- Model performance monitoring
- Alerting
What's Included
Live instructor-led online session
Small cohort (max 12 delegates)
Course materials & code samples
CPD accredited certificate
Post-session recording (30 days)
Q&A with your instructor
£695+ VATEnrol Now Book for a team
per person, excluding local tax.
7 hours (1 day)
Next: Tue, 14 Apr 2026
8 seats remaining
Advanced level
4/12 seats filled
CPD accredited · Full refund 14 days before