AI Campus — Intelliscan Standards Institute

Six-module course on AI in African energy, climate and infrastructure — grid management, mini-grids, climate risk, predictive maintenance, and AI governance under the Electricity Act 2023.

An ADBOK-aligned course on artificial intelligence in African agriculture and food systems. Built for students, agronomists, agritech operators, donor program officers, and ministry staff working in the continent's largest employer. Six weeks. Anchored in real deployments at Nigerian, Kenyan, and pan-African agritech companies. Aligned to NUC CCMAS digital-skills requirements and the African Union Continental AI Strategy.

AI for Educators is a six-week sector course for Nigerian teachers, lecturers, vocational and TVET instructors, training managers, instructional designers, school administrators, and education policy professionals who want to engage with AI seriously in 2026. The course assumes you understand what AI is at a conceptual level (AI Foundations) and takes you from there into the live questions in your classroom and institution: how to use AI for lesson design and content creation, how to deploy AI tutoring responsibly, how to redesign assessment in an age when every student has a chatbot, how to teach AI literacy to students from JSS1 to final-year university, and how to build responsible AI practice at the institutional level. Every module is grounded in Nigerian education reality — large class sizes, infrastructure variance, the WAEC/NECO/JAMB system, the FUE/state university split, the TVET sector, NUC oversight, and the spectrum of student backgrounds. You will leave the course able to redesign your teaching, advise your institution credibly, and engage parents, students, and the press on AI in education without hype or fear.

Prerequisites: AI Foundations (AIF-101) or equivalent conceptual understanding. The course does not assume programming skill, but assumes working familiarity with classroom or teaching practice at primary, secondary, tertiary, vocational, or training level.

AI for Developers is a six-week technical course for engineers, data scientists, ML practitioners and tech leads who want to build with AI competently in 2026. The course assumes you understand what AI is at a conceptual level (AI Foundations) and have used AI tools personally (AI Tools for Work), and takes you from there into how AI systems are actually engineered: foundation-model APIs, prompting at production quality, retrieval-augmented generation, agents and tool use, fine-tuning and small models, and the operational discipline — evaluation, observability, safety and compliance — that separates demos from systems people depend on. Every module is grounded in code-level decisions, real cost numbers, and the Nigerian developer’s reality of bandwidth, naira budgets, vendor availability, and the Nigeria Data Protection Act. You will leave this course able to design and ship an AI-powered feature, defend the choices you made, and operate it responsibly in production.

Prerequisites: AI Foundations (AIF-101) and AI Tools for Work (AITW-101), or equivalent. You should also be a working software engineer or data scientist — comfortable reading and writing code in at least one mainstream language (Python or JavaScript/TypeScript recommended), comfortable with REST APIs, the command line, and git. This is not a programming primer.

AI for Business Leaders is a six-week strategy course for Nigerian executives, founders, managers and board members. It assumes you have completed AI Foundations and AI Tools for Work; this course is about the decisions only the leader can make. You will learn how to evaluate AI vendors and avoid the procurement traps, how to build an AI strategy that survives the next three years, how to govern AI in an organisation operating under the Nigeria Data Protection Act and the National AI Strategy, how to lead the change in talent, culture and performance management that AI demands, and how to actually measure whether the AI investment is paying back.

Prerequisites: AI Foundations (AIF-101) and AI Tools for Work (AITW-101), or equivalent practical understanding.

By the end of this course you will be able to:

• Evaluate AI vendors and procurement proposals with confidence.
• Design and pressure-test an AI strategy and roadmap for your organisation.
• Build the governance and risk framework that satisfies the NDPA, the NAIS, and your board.
• Lead the talent, culture and performance changes that determine whether AI investment actually pays off.
• Measure ROI in a way that captures both visible productivity gains and the harder-to-see value.

A plain-language introduction to artificial intelligence built for learners with no prior technical background. Learn what AI is and is not, how machine-learning models are trained, how AI is being deployed across Nigerian banking, health, agriculture, and government, and how to evaluate AI claims you encounter in business.

Introduction to Artificial Intelligence Governance is a six-week, Foundation-level course built for the Nigerian context. It explains what AI governance is, why an organization needs it before AI is deployed at scale, and how the moving parts — the AI lifecycle, enterprise risks, responsible-AI principles, the global standards landscape, and accountable governance structures — fit together. The treatment is practical and opinionated, grounded in the Nigeria Data Protection Act 2023, the NDPC, NITDA and the National AI Strategy, alongside accurate accounts of ISO/IEC 42001, the NIST AI Risk Management Framework and the EU AI Act.

By the end you will be able to define AI governance to a board, map governance across the AI lifecycle, build a basic AI risk register, apply responsible-AI principles, compare the major global frameworks, and sketch a foundational governance structure for your own organisation.

For: Executives, project and product managers, compliance and risk teams, public-sector and university leaders, and professionals beginning the path to the Certified AI Governance Associate (CAIGA) certificate.

Responsible AI Implementation is a six-week, intermediate course on the unglamorous work of turning AI ethics principles into operating controls. It is about the gap between a “Responsible AI” slide and an AI system that is actually fair, explainable, overseen by a named human, and auditable — and how a Nigerian organisation closes that gap under the NDPA 2023, a watching NDPC, and sector regulators such as the CBN, NAFDAC and NCC.

You will learn to mitigate bias, operationalise transparency and explainability, design human-in-the-loop oversight, stand up an ethics review board, conduct AI impact assessments across the lifecycle, and run an AI ethics audit. Throughout, international frameworks — ISO/IEC 42001, the NIST AI RMF, the OECD AI Principles, the UNESCO Recommendation and the EU AI Act — are treated as the toolkit, with the application localised to Nigeria.

For: AI governance professionals, compliance and risk officers, internal auditors, data scientists and AI engineers, project managers, and public-sector and university leaders moving from AI principles to operational accountability.

AI Governance Policy Development is a six-week intermediate course on writing the policies that actually govern AI inside an organisation — acceptable use, generative-AI controls, risk and compliance, responsible-AI and ethics, vendor and data governance, and incident response. It is built for the Nigerian context: the Nigeria Data Protection Act 2023, a watching NDPC and NITDA, the National AI Strategy, and sector regulators such as the CBN, NAFDAC and NCC. You will not learn to admire policies — you will learn to draft enforceable ones.

Across the course you build a practical deliverable set: an enterprise AI governance handbook and a library of policy templates you can take back to your own organisation and put to work.

For: Compliance officers, risk managers, internal auditors, AI and project leads, legal and policy teams, and public-sector, university and healthcare administrators who must write or own AI policy rather than merely cite it.

AI Regulatory Compliance & Readiness is a six-week, advanced course for practitioners who must keep an organisation’s artificial-intelligence systems on the right side of the law and ready for scrutiny. It moves from the principles behind AI regulation, through the EU AI Act and the global patchwork of AI laws, into privacy and data protection under the Nigeria Data Protection Act 2023 and the GDPR, then into the concrete obligations that attach to high-risk AI, the documentation and audit trail that proves compliance, the monitoring and reporting duties that continue after launch, and finally what happens when a regulator comes knocking.

By the end you will be able to explain why AI is regulated and how the major regimes are built, classify a system under the EU AI Act’s risk tiers and identify its obligations, reconcile AI governance with the NDPA and GDPR, assemble the technical documentation a regulator expects, run post-market monitoring and meet reporting duties, respond competently to an investigation, and design an enterprise compliance-readiness programme that holds up under the NDPC, the CBN, NAFDAC or the NCC.

For: Compliance officers, data protection officers, regulatory and legal professionals, risk managers, AI and product leaders, internal auditors, and public-sector oversight staff in Nigerian organisations preparing for AI regulation and regulator scrutiny.

AI Vendor Risk Management is an advanced, six-week programme for practitioners who govern the AI their organisation buys rather than builds. Most Nigerian enterprises consume AI through foreign cloud platforms, scoring APIs, embedded vendor features and resold models — and the risk does not transfer with the supplier. This course turns that uncomfortable fact into a working discipline: how to assess a vendor before signing, what to demand in the contract, how to govern cloud and API dependencies, how to monitor a relationship you do not control, and how to run all of it as a programme an auditor and the NDPC can verify.

It assumes you already understand AI governance fundamentals and ISO/IEC 42001 at a high level. It builds the third-party layer on top: due diligence, procurement, contract terms, cloud and API governance, ongoing assurance, and enterprise programme design, anchored in the Nigeria Data Protection Act 2023 and the expectations of the NDPC, NITDA, the CBN and sector regulators.

For: Vendor-risk and procurement leads, third-party risk managers, compliance and DPO functions, internal auditors, CISOs and AI governance owners in banks, fintechs, telcos, hospitals, public agencies and any organisation whose AI capability is largely purchased.

ISO/IEC 42001 Internal Auditor is an advanced, six-week professional course that trains you to plan and conduct internal audits of an Artificial Intelligence Management System (AIMS). Grounded in ISO/IEC 42001 and the auditing discipline of ISO 19011, it takes you from audit principles through planning, evidence collection and control testing to writing nonconformities, driving corrective action, and running a full simulated AI governance audit in a Nigerian organisation.

The course localises every technique to the Nigerian setting — the Nigeria Data Protection Act 2023, the NDPC, NITDA and sector regulators such as the CBN, NAFDAC and NCC — while keeping the ISO 42001 and ISO 19011 audit facts accurate. By the end you will be able to audit an AIMS independently, defensibly, and in a way an external certification body would recognise.

For: Internal auditors, compliance officers, risk managers, AI governance and ISO professionals, cybersecurity auditors, and public-sector oversight teams preparing to audit AI governance or to support certification.

The Chief AI Governance Officer Programme is the campus’s executive flagship: a six-week leadership programme for the person who will own artificial intelligence governance at the most senior level of a Nigerian enterprise. It assumes you already understand what governance is and asks the harder question — how do you lead it across an entire organisation, answer to a board, satisfy the NDPC and sector regulators, and keep the enterprise both safe and competitive while AI reshapes it.

This is not a controls course. It is about strategy, accountability, operating models, regulatory posture, crisis leadership and organisational change — the work of a Chief AI Governance Officer (CAIGO) who sits in the C-suite and is answerable when AI helps or harms.

For: Chief AI governance officers, chief risk and compliance officers, general counsel, chief data and digital officers, and the executives and non-executive directors who appoint and oversee them.

Advanced AI Governance Strategy is a six-week executive programme for directors, C-suite leaders and senior governance owners who must steer an organisation’s use of AI from the top. It is not a controls course. It is about strategy, operating models, accountability and oversight: how a board sets the appetite, how the executive builds an operating model that scales, and how leadership turns “we have a policy” into a governed enterprise capability under the Nigeria Data Protection Act 2023 and a watching NDPC.

By the end you will be able to frame AI governance as a board-level strategic concern, choose and defend an operating model, sequence a multi-year governance transformation, read the maturity of your own organisation, lead responsibly under pressure, design the metrics and reporting a board actually needs, and reason about where enterprise AI governance is heading.

For: Board members, CEOs, CFOs, chief risk and compliance officers, Chief AI and data officers, and senior public-sector and bank executives accountable for AI to a board, a regulator or the public.

Generative AI Governance is a six-week, specialisation-level course for practitioners who must govern the wave of generative tools — chatbots, copilots, image and document generators — now spreading through Nigerian organisations. It moves beyond general AI governance to the specific, awkward problems generative systems create: confident falsehoods, leaked data through prompts, synthetic content with no provenance, copyright exposure, and adoption that outruns any policy. It teaches what to govern, which controls actually work, and how to assure a board and the NDPC that an enterprise GenAI programme is under control.

By the end you will be able to frame the governance problem generative AI poses, run a GenAI risk assessment, design prompt and safety controls, govern AI-generated content and its copyright and IP exposure, deploy responsibly with monitoring and assurance in place, and read where regulation and practice are heading.

For: AI governance leads, risk and compliance officers, data protection officers, internal auditors, product and engineering leaders, legal counsel, and public-sector and enterprise teams rolling out copilots and generative tools under the NDPA 2023 and a watching NDPC.

AI Governance for Law Enforcement is a six-week specialisation for those who must govern artificial intelligence inside policing, security and criminal-justice institutions, built for the Nigerian context. It moves past general principles into the hard cases: facial recognition at a checkpoint, a predictive-policing map that concentrates patrols on one community, an automated watch-list that flags the wrong citizen. By the end you will be able to design oversight that holds up in court and before the public, weigh operational need against constitutional rights under the 1999 Constitution and the Nigeria Data Protection Act 2023, and run an accountable law-enforcement AI programme that the NDPC, the National Human Rights Commission and an ordinary Nigerian can trust.

For: Police technology and intelligence leads, oversight-body and ministry officials, data protection officers in security agencies, internal-affairs and audit staff, civil-society monitors and legal advisers working on policing and surveillance.

AI Governance for Energy & Utilities is a six-week specialisation for the people who keep Nigeria’s lights on and its taps running. It takes the discipline of AI management systems and applies it where the consequences are physical: a grid that must balance in real time, assets that fail dangerously when neglected, and a sector watched by NERC, NITDA and the NDPC. By the end you will be able to govern AI across generation, transmission, distribution and retail — from smart-grid optimisation and predictive maintenance to renewable forecasting and operational safety — and run an enterprise energy AI programme that survives an outage, an audit and a regulator’s questions.

For: DisCo and GenCo engineers and risk leads, grid and control-room operators, asset and reliability managers, energy cybersecurity teams, renewable IPP analysts, and the compliance and governance staff who answer to NERC and the NDPC.

This is a Specialisation-level course: it assumes you already grasp the basics of AI governance and want to apply them to the specific, high-consequence reality of power and utilities.

AI Governance for Manufacturing is a six-week specialisation for people who must govern artificial intelligence on the factory floor — not as a slide deck, but as machines that move, weld, sort, predict and decide in real time. It builds on management-system thinking (ISO/IEC 42001) and applies it to the hard realities of industrial AI: smart factories, robots that share space with people, predictive maintenance, supply chains, cybersecurity for operational technology, and the assurance that lets a board and a regulator trust all of it. The Nigerian context runs throughout — the NDPA 2023, NITDA, and the Standards Organisation of Nigeria (SON) — alongside accurate use of ISO, NIST and the EU AI Act.

By the end you will be able to scope a manufacturing AI governance programme, classify and control industrial AI risk, govern robots and predictive systems safely, secure AI-enabled operational technology, and run an audit and assurance cycle that survives scrutiny.

For: Plant managers, quality and EHS leaders, OT and IT security staff, industrial engineers, risk and compliance officers, and AI/automation leads in Nigerian and African manufacturing.

AI Governance for Insurance is a six-week specialisation for the people who decide how AI underwrites, prices, pays and polices risk. It moves past general principles into the specific decisions an insurer makes every day — who is offered cover, at what premium, whose claim is fast-tracked, whose claim is flagged as fraud — and shows how to govern the models now sitting behind those decisions. The course is built for the Nigerian context: the Nigeria Data Protection Act 2023, a watching NDPC, the National Insurance Commission (NAICOM) as sector regulator, and the practical reality of selling and settling insurance across Lagos, Abuja, Kano and beyond.

By the end you will be able to identify where AI already shapes insurance decisions, govern underwriting and claims models, oversee fraud and risk-modelling systems lawfully, run a bias and impact assessment on a pricing tool, meet NAICOM and NDPC expectations with auditable records, and stand up a full enterprise insurance AI governance programme.

For: Chief risk and compliance officers in insurance, heads of underwriting and claims, actuarial and data-science leads, internal auditors, data protection officers, and the executives accountable for how policyholders are treated.

AI Safety Engineering is a six-week specialisation for the technical practitioners who build, deploy and assure AI systems where failure has real-world consequences. It moves past principles into engineering: how AI systems fail, how to design controls that catch failure before it reaches a person, how to test a system adversarially, how to suppress harmful outputs, and how to monitor a live system so safety is a measured property rather than a hope. By the end you will be able to reason about failure modes, build a safety control stack, run a red-team, and stand up a safety assurance programme that an engineer, an auditor and the NDPC could all trust.

For: ML engineers, data scientists, MLOps and platform engineers, technical risk and assurance leads, and AI product owners deploying safety-critical AI in Nigerian banking, health, telecoms and public-sector contexts.

This is a Specialisation-level course. It assumes you can read code and reason about models; it teaches you to make them safe under the NDPA 2023, NITDA guidance, and international practice such as the NIST AI Risk Management Framework and ISO/IEC 42001.

AI Governance for Higher Education is a six-week specialisation for the people who run Nigerian universities, polytechnics and colleges of education. It takes the general discipline of AI governance and applies it where the stakes are particular: teaching, assessment, student records, research integrity and institutional administration. It covers what good governance looks like inside an academic institution, why each control exists, and what it takes to stand one up under the Nigeria Data Protection Act 2023, a watching NDPC, and the expectations of the National Universities Commission.

By the end you will be able to design an institutional AI governance framework, write defensible policies on academic integrity and student data, govern faculty and research use of AI, and lead an institution-wide programme from first policy to mature practice.

For: Vice-chancellors, rectors, provosts, registrars, deans, heads of ICT and data protection, quality-assurance officers, librarians, and senate or council members responsible for AI policy in tertiary institutions.

AI Governance for Healthcare is a six-week specialisation for the people responsible for AI where the stakes are a patient’s body, not a customer’s click. It moves past general principles into the specific decisions healthcare makes — who gets triaged first, which scan is flagged, which drug dose is suggested, who is predicted to deteriorate — and shows how to govern the models now sitting behind those decisions. The course is built for the Nigerian context: the Nigeria Data Protection Act 2023 and a watching NDPC, the medical-device and product oversight of NAFDAC, the professional duties enforced by the Medical and Dental Council of Nigeria, the claims and coverage role of the NHIA, and the daily reality of teaching hospitals in Lagos, Ibadan and Abuja.

By the end you will be able to identify where AI already shapes clinical and administrative decisions in your facility, navigate the regulatory and patient-data landscape, run a clinical risk and impact assessment on a diagnostic or triage tool, embed responsible-AI safeguards into care pathways, audit a deployed healthcare AI system, manage an AI incident that reaches a patient, and stand up a full enterprise healthcare AI governance programme.

For: Hospital medical directors and clinical governance leads, health-system quality and safety officers, data protection officers, biomedical and health-informatics teams, hospital risk and compliance managers, HMO and NHIA-facing administrators, and the executives accountable for patient safety.

Aviation is the most safety-critical environment in which artificial intelligence is now being deployed — in flight operations, air traffic management, predictive maintenance, and airport security. When an AI system shapes a decision in this sector, the cost of a failure is measured in lives, not refunds. This specialisation prepares professionals to govern AI in aviation responsibly, in line with international civil-aviation safety practice and Nigeria’s regulatory framework.

Localised to Nigeria — the Nigerian Civil Aviation Authority (NCAA), the Nigerian Airspace Management Agency (NAMA), and the Federal Airports Authority of Nigeria (FAAN) — while keeping ICAO, ISO/IEC 42001 and NIST AI RMF practice accurate. It is for aviation safety, operations, engineering, security and compliance professionals who must oversee AI without compromising the sector’s hard-won safety culture.

AI Governance for Africa & Emerging Markets is a six-week specialisation for the people who must govern artificial intelligence where the textbooks were not written for them. It takes the international toolkit — ISO/IEC 42001, the NIST AI Risk Management Framework, the EU AI Act — and asks the harder question: how do you govern AI well in a country with thin connectivity, limited compute, a young data-protection regime, scarce specialist skills and a regulator still finding its feet? The answer is not to copy a European framework wholesale, nor to abandon standards as a luxury, but to adapt them to the realities of an emerging market without losing what makes them work.

The course is anchored in Nigeria — the Nigeria Data Protection Act 2023, the NDPC, NITDA and the National Artificial Intelligence Strategy — and set in the wider African frame of the African Union Continental AI Strategy, the Malabo Convention and Smart Africa. By the end you will be able to diagnose the governance constraints particular to emerging markets, develop a national or organisational AI policy that fits its context, govern public-sector and infrastructure realities honestly, and lead a programme that delivers economic value without importing harm.

For: Policy advisers and regulators, public-sector AI leads, development-agency programme staff, governance officers in banks, telcos and start-ups, and academics shaping AI strategy across Nigeria and the continent.