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Computing and Information Technology

Governance and Compliance in AI Governance, Responsible AI & ISO 42001 Training Course in Kampala, Uganda

Classroom training in Kampala · next cohort Nov 2, 2026 · from USD 3,800

Organisations are deploying machine learning and generative tools faster than their policies can keep up, and biased outputs, data leakage, opaque decisions and regulatory scrutiny are already costing money and trust. Boards, auditors and customers now ask for evidence that AI is governed, not merely used. Across ten days, participants learn to establish that evidence through a management system built on ISO/IEC 42001.

Upcoming sessions in Kampala

Kampala, Uganda

Nov 2 – 13, 2026

$3,800

Register

Kampala, Uganda

Nov 30 – Dec 11, 2026

$3,800

Register

Kampala, Uganda

Dec 28, 2026 – Jan 8, 2027

$3,800

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Kampala, Uganda

Jan 25 – Feb 5, 2027

$3,800

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At a Glance

Training in Kampala, Uganda

Kampala is Uganda's capital and the base of its government, banks and growing oil and gas sector.

More about training in Kampala →
Format
Classroom, in Kampala
Duration
Mon - Fri (10 Days)
Fee
USD 3,800
Next start dates
Nov 2, 2026, Nov 30, 2026, Dec 28, 2026
Certificate
Certificate of Completion
Airport
Entebbe International (EBB), about 40 km from Kampala
Time zone
East Africa Time (UTC+3)
Currency
Uganda shilling (UGX). Fees are listed in USD.
Business districts
Nakasero, Kololo and Kampala Central

About this course

Artificial intelligence now influences credit decisions, hiring, health triage, fraud detection, public services and customer interaction. With that reach comes accountability. Regulators across several regions are drafting or enforcing rules on automated decision making, and customers and investors expect organisations to show who owns each AI system, what data it uses, how it has been tested and what happens when it fails. ISO/IEC 42001 provides a certifiable management system framework for exactly this purpose.

This ten-day programme takes participants from governance principles to a working, auditable AI management system. The opening days establish context: AI concepts for non-engineers, the risk landscape, responsible AI principles and the structure of the standard. Subsequent sessions build the system component by component, including policy, scope, roles, objectives, impact assessments, data and model lifecycle controls, supplier management, documentation and awareness. The second week concentrates on assurance: monitoring and metrics, incident response, generative AI specific controls, internal audit, management review, corrective action and certification readiness.

Participants work throughout on a case organisation, producing artefacts such as a gap analysis, risk register, statement of applicability and audit plan. The final days integrate everything in a project presented to the group for challenge and feedback.

Training Objectives

By the end of the programme, participants will be able to:

  • Explain the principles of responsible AI and the governance models used to apply them.
  • Interpret the clauses and Annex controls of ISO/IEC 42001 and plan their implementation.
  • Define the scope, policy, roles and objectives of an AI management system.
  • Conduct AI risk and impact assessments covering fairness, safety, privacy and security.
  • Establish data governance and model lifecycle controls from design to retirement.
  • Assess third-party and generative AI providers, and design monitoring and incident response for AI systems.
  • Plan internal audits and management reviews against the standard and prepare the organisation for external certification.
  • Map the management system to applicable laws and sector expectations.

What you'll learn

Explain the principles of responsible AI and the governance models used to apply them.
Interpret the clauses and Annex controls of ISO/IEC 42001 and plan their implementation.
Define the scope, policy, roles and objectives of an AI management system.
Conduct AI risk and impact assessments covering fairness, safety, privacy and security.
Establish data governance and model lifecycle controls from design to retirement.
Assess third-party and generative AI providers, and design monitoring and incident response for AI systems.
Plan internal audits and management reviews against the standard and prepare the organisation for external certification.
Map the management system to applicable laws and sector expectations.

Key Takeaways

Participants leave with:

  • A gap analysis against ISO/IEC 42001 for a chosen organisation.
  • A draft AI policy set and governance charter.
  • An AI risk register and impact assessment template.
  • A statement of applicability with justified control selection.
  • A supplier and generative AI due diligence checklist.
  • An internal audit programme and sample audit report.
  • A certification readiness roadmap with owners and dates.

Training Methodology

The programme is cumulative, with each day adding a component to a case-based management system. Delivery includes:

  • Expert-led explanation of standard requirements in practical terms
  • Daily labs producing governance artefacts and registers
  • Review of anonymised AI failures and near misses
  • Mock audits and incident simulations
  • A final project defended before the group
FAQ

Frequently Asked Questions About Governance and Compliance in AI Governance, Responsible AI & ISO 42001 Training Course in Kampala

Everything you need to know about this course before you register.

Governance and Compliance in AI Governance, Responsible AI & ISO 42001 Training Course runs as classroom training in Kampala, Uganda, in Monday-to-Friday cohorts that start every four weeks. The venue, daily timings and joining details are sent in your Joining Instructions email ahead of the start date.

Still have questions about Governance and Compliance in AI Governance, Responsible AI & ISO 42001 Training Course in Kampala? Chat with an advisor·Visit the full FAQ

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Managing Director

They facilitated our strategy review, we improved departmental KPI alignment by 35% and reduced operational bottlenecks significantly.

David Oketch

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Strategy Lead

Employee engagement scores increased following the leadership training program. The difference in accountability culture is evident.

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