Bachelor in Artificial Intelligence and Technology
Build intelligent systems from first principles — mathematics, machine learning and responsible deployment.
A three-year, build-led programme that develops engineers who understand intelligence from first principles — the mathematics beneath the models, the systems that carry them, and the responsibility that must govern them. You do not merely use AI; you build, evaluate and deploy it.
No passive lectures. A curriculum built for how the mind actually learns.
Every course runs as a live, high-intensity seminar. Preparation happens before class; class time is spent thinking, defending ideas and applying them. Progression is governed by demonstrated mastery — never by age or time served.
Engage independently with curated readings, problems and worked examples before every seminar.
Small live seminars built on structured discussion, argument and immediate faculty feedback — no lecturing.
Transfer each concept to real problems — ventures, research, systems and civic projects grounded in your own context.
Advance only when you can explain, defend and use what you know. Recorded oral explanation is central from the earliest years.
- Linear algebra, probability and optimisation for AI
- Programming and data structures
- How computers and data really work
- First shipped project
- Machine learning: theory and practice
- Deep learning and modern architectures
- Data engineering and MLOps
- AI ethics, safety and governance
- Advanced and applied ML
- Human-centred and responsible deployment
- Capstone build — a working AI product
- Technical defence and evaluation
Transferable habits of thought, practised in every course
Rather than memorisation, Simo trains a durable set of thinking skills that transfer across subjects, industries and a lifetime. They are introduced early, revisited deliberately, and assessed continuously.
Logic, quantitative and algorithmic thinking to frame, decompose and solve problems.
Framing hypotheses, designing evidence, reading data and reaching defensible conclusions.
Writing, speaking, visual and multilingual expression that persuades and clarifies.
Multiple causality, trade-offs and second-order effects in complex human and technical systems.
Combining ideas across disciplines to produce original, useful and beautiful work.
Judgement under real stakes — responsibility, fairness and the human consequences of decisions.
- Mathematics for AI
- Programming & data structures
- Machine learning
- Deep learning
- AI systems & ethics
- Capstone build
- Implement and evaluate ML models
- Reason about algorithms and complexity
- Ship a working AI system responsibly
The Capstone Build is a working AI system you design, train, evaluate and deploy end-to-end — with an honest account of its limits, biases and impact. You defend it technically and ethically before faculty and industry reviewers.
ML engineer, data scientist, AI product roles.
Recognised secondary qualification or Foundation & Accelerated Entry Pathway.
Africa's next AI builders start here. Fully online, in French or English, on modest hardware — with regional tuition and instalments from about €275, by card or Mobile Money. Your capstone solves a problem you can see around you, so the skills convert immediately into local and remote opportunity.