Deploying and Operating Machine Learning Models
A model that works in a notebook is not yet a working system. This course covers what it takes to run a model in production: packaging, serving, monitoring for drift and retraining without breaking what depends on it.
Course outline
What this programme covers, module by module.
- 01Why models fail after they leave the notebook
- 02Packaging, dependencies and reproducible environments
- 03Serving patterns: batch, real time and embedded
- 04Versioning models, data and code together
- 05Monitoring for drift, degradation and data quality breaks
- 06Retraining, shadow deployment and safe rollout
- 07Governance, audit and accountability for a live model
What you will gain
- Package a model so it can be deployed repeatably
- Choose a serving pattern suited to the use case
- Version models, data and code together
- Monitor a live model for drift and degradation
- Retrain and roll out safely without breaking consumers
- Establish the governance a production model requires
Who should attend
- Data scientists moving models into production
- Machine learning and data engineers
- DevOps and platform engineers
- Technical leads owning model based systems
Upcoming sessions
| Date | City | Duration | Fees | Book |
|---|---|---|---|---|
| 26 to 30 Oct 2026 | Johannesburg | 5 Days | R18,000 | |
| 9 to 13 Nov 2026 | London | 5 Days | US$1,800 | |
| 30 Nov to 4 Dec 2026 | Dubai | 5 Days | US$1,800 | |
| 11 to 15 Jan 2027 | Pretoria | 5 Days | R18,000 | |
| 25 to 29 Jan 2027 | Durban | 5 Days | R18,000 | |
| 5 to 9 Apr 2027 | Cape Town | 5 Days | R18,000 | |
| 7 to 11 Jun 2027 | Johannesburg | 5 Days | R18,000 |
Fees are per delegate and exclude VAT. Public intakes are confirmed once minimum numbers are met. We also deliver this course on your own schedule, in-house or live online.
Enquire about this course
Register your team or ask for a tailored in-house quote. We reply within one working day.
WhatsApp usCourse brochure (PDF)- Fees from
- R18,000 per delegate
- Duration
- 5 Days
- Field
- Artificial Intelligence & Emerging Technology
- Formats
- In-house, public, online
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