Data Privacy in Artificial Intelligence Systems
Training and running models on personal information raises duties that ordinary system design does not. This course covers lawful basis, minimisation and the specific privacy risks that model based systems create.
Course outline
What this programme covers, module by module.
- 01Where model based systems create novel privacy risk
- 02Lawful basis for training and for inference
- 03Minimisation, purpose limitation and retention of training data
- 04Anonymisation, pseudonymisation and re identification risk
- 05Data subject rights against a trained model
- 06Privacy preserving techniques and their trade offs
- 07Impact assessments and documenting decisions
What you will gain
- Establish a lawful basis for using personal data in models
- Apply minimisation and purpose limitation to training data
- Assess re identification risk in supposedly anonymous data
- Handle data subject rights against a trained model
- Apply privacy preserving techniques where appropriate
- Document privacy decisions for regulators
Who should attend
- Privacy and compliance professionals
- Data scientists and engineers
- Information officers
- Risk and audit staff covering model use
Upcoming sessions
| Date | City | Duration | Fees | Book |
|---|---|---|---|---|
| 3 to 4 Nov 2026 | Cape Town | 2 Days | R10,000 | |
| 23 to 24 Nov 2026 | Johannesburg | 2 Days | R10,000 | |
| 7 to 8 Dec 2026 | London | 2 Days | US$1,100 | |
| 11 to 12 Jan 2027 | Dubai | 2 Days | US$1,100 | |
| 22 to 23 Feb 2027 | Pretoria | 2 Days | R10,000 | |
| 26 to 27 Apr 2027 | Durban | 2 Days | R10,000 | |
| 12 to 13 Jul 2027 | Cape Town | 2 Days | R10,000 |
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
- R10,000 per delegate
- Duration
- 2 Days
- Field
- Artificial Intelligence & Emerging Technology
- Formats
- In-house, public, online
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