All 52 AI Campus courses in one place — from AI Foundations at GH₵140 to the Chief AI Governance Officer Programme. Pick a course, pay securely with Paystack, and you're in.
Choose below and pay securely by card, bank transfer, or USSD through Paystack. Instalment option available on courses from GH₵250.
Right after payment we'll point you to the AI Campus to create your student account — use the same email you paid with.
We activate your course access — usually much faster — and email you when it's ready. Finish the course, earn a verifiable certificate.
Professional credentials awarded by the Institute, built on the ADBOK framework. Assessed by examination against a published pass mark, and verifiable on the public registry.
The gateway credential for anyone entering the AI data profession. Six modules covering ADBOK terminology, how annotation projects actually run, annotation methods across text, image, audio and video, data quality fundamentals, AI ethics and responsible labelling, and the responsibilities of the human in the loop. Forty lessons and three practice exams scored against the real 70% pass mark. No prerequisites.
The practitioner credential for people who execute complex, multi-modal annotation work across text, image, audio and video. Six modules covering annotation workflows, inter-annotator agreement methodology, edge-case handling, NLP and computer-vision labelling standards, and quality metrics. Practice exams are scored against the real 72% pass mark. Prerequisite: AAP or demonstrated equivalent experience.
Foundation + sector courses for students, national service personnel, and working professionals. Start here.
Plain-language introduction to AI for learners with no technical background — what AI is, how it is used across Ghanaian banking, health, agriculture, and government.
Hands-on mastery of ChatGPT, Claude, Gemini, and the AI tools already at work — prompts, workflows, and the privacy questions to ask.
Practical data literacy for non-technical professionals — question dashboards and reports, tell correlation from causation, work with spreadsheets and BI tools, and use AI to speed up analysis without being fooled by it.
Six-week strategy course for executives, founders, and managers — vendor evaluation, AI strategy, governance, talent, and measuring ROI.
The responsible-AI deep dive — where AI causes harm, what the Data Protection Act 843 requires, and how to build governance into an organisation.
Technical course for engineers — foundation-model APIs, RAG, agents, fine-tuning, and the discipline that separates demos from production systems.
For clinicians, administrators, and public-health professionals — clinical AI evidence, Ghana FDA and Data Protection Commission expectations, responsible deployment.
For teachers, lecturers, and administrators — lesson design with AI, responsible AI tutoring, assessment redesign, and AI literacy from JSS1 up.
For civil servants and policy advisors — AI in Ghanaian MDAs and MMDAs, citizen-facing AI under the Data Protection Act 843, procurement, and Ghana's national AI strategy.
ADBOK-aligned course on AI in African agriculture — real deployments across Ghanaian, Kenyan, and pan-African agritech.
AI in African financial services — credit decisioning, fraud and AML, RegTech, and AI risk governance under Bank of Ghana and Data Protection Act 843.
AI in African energy and infrastructure — grid management, mini-grids, climate risk, and governance under the Electricity Act 2023.
AI in African creative industries — Nollywood production, Afrobeats, journalism, advertising, and rights for African creators.
Entry point into AI governance: the standards, the frameworks, the vocabulary.
The world's first AI Management System standard — what it requires, why, and what it takes to stand one up in a Ghanaian organisation.
What AI governance is and why you need it before AI scales — lifecycle, risk registers, responsible-AI principles, global frameworks.
Govern, Map, Measure, Manage — the NIST AI RMF taught for the Ghanaian context, alongside ISO/IEC 42001 and the Data Protection Act 843.
From principles to practice: policy writing, risk management, responsible implementation.
Write the policies that actually govern AI — acceptable use, generative-AI controls, vendor governance, incident response. Leave with a template library.
Run AI risk assessments, build risk registers, write defensible impact assessments, and stand up monitoring — anchored to NIST and ISO/IEC 42001.
Close the gap between a Responsible AI slide and a system that is fair, explainable, overseen, and auditable under the Data Protection Act 843.
Practitioner-grade programmes: auditing, red teaming, incident response, ISO/IEC 42001 delivery.
The working craft of the AI auditor — scoping engagements, testing controls, EU AI Act / GDPR / Data Protection Act 843 mapping, audit readiness.
Plan and conduct internal audits of an AI Management System — ISO 19011 discipline, nonconformities, a full simulated audit.
The Institute's flagship professional certification — lead a full enterprise AIMS implementation to certification readiness.
Govern the AI your organisation buys — due diligence, contract terms, cloud and API governance, ongoing assurance the Data Protection Commission can verify.
Authorised adversarial testing of AI systems — threat modelling, prompt-injection testing, robustness evaluation, enterprise red-team programmes.
Keep AI on the right side of the law — EU AI Act risk tiers, Data Protection Act 843 and GDPR, technical documentation, and surviving an investigation.
For the people who get the call when AI goes wrong — classification, containment, Data Protection Commission notification duties, crisis communication.
Board-facing leadership programmes for the people accountable for AI at the top.
Board-facing programme on the decisions only leaders can make — ethical posture, accountability, and trust as strategy.
For directors and C-suite — operating models, board oversight, and sequencing a multi-year governance transformation.
Give the board and the regulator evidence-backed confidence — assurance functions, AI audits, governance metrics.
The executive flagship — own AI governance at the most senior level: strategy, regulatory posture, crisis leadership.
Sector-specific governance: one industry, six weeks, governed properly.
Hands-on assurance of chatbots and copilots — hallucination detection, jailbreak testing, evaluation suites, live monitoring.
Adapt the international toolkit to emerging-market reality — thin connectivity, young regulators, the AU Continental AI Strategy.
Govern AI that moves people and goods — ISO 26262, SOTIF, UL 4600, and the EU AI Act high-risk regime on Ghanaian roads.
AI in the most safety-critical sector — flight operations, air traffic, predictive maintenance, NCAA / NAMA / FAAN context.
Governance inside the Ghanaian state — national policy, procurement, public trust, and an audit-and-assurance capstone.
Where the stakes are a patient's body — triage and diagnostic AI, Ghana FDA and MDC duties, clinical impact assessment.
Model risk discipline for banks and fintechs — credit and fraud models, Bank of Ghana examination readiness, vendor accountability.
For university leaders — academic integrity policy, student data, research use of AI, GTEC expectations.
Responsible governance where decisions touch sovereignty and life — human oversight, assurance, international humanitarian law.
For technical practitioners — failure modes, safety control stacks, adversarial testing, and measured safety in production.
Govern the algorithms running urban life — traffic, surveillance, service portals, vendor accountability, public trust.
Underwriting, pricing, claims, and fraud models governed lawfully — NIC and Data Protection Commission expectations with auditable records.
Bring network AI under control — routing, credit scoring, SIM fraud models, NCC licence conditions, subscriber fairness.
Industrial AI governed on the factory floor — smart factories, robots, OT security, GSA and NITA context.
Govern AI in the systems a nation cannot afford to fail — power, water, ports, telecoms, the Cyber Security Authority and CII regime.
AI across generation, transmission, and retail — grid optimisation, predictive maintenance, PURC and Data Protection Commission oversight.
Govern the algorithms behind hiring, promotion, and monitoring — bias assessment, Labour Act, tribunal-ready records.
Facial recognition, predictive policing, watch-lists — oversight that holds up in court and before the public.
AI in aid and development programming — donor accountability, impact assessment, SDG alignment, vulnerable populations.
Govern the GenAI wave — hallucination, prompt data leaks, synthetic content, copyright exposure, enterprise controls.
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