Artificial intelligence projects are not managed like traditional technology projects: uncertainty is higher, results are not always predictable, and success depends as much on data as on the people who interpret it. This course provides a practical roadmap for leading AI projects from end to end, combining technical fundamentals, management tools, and a critical look at risks and ethics.

Across six modules, you will learn to identify what makes an AI project unique compared to a conventional one, evaluate the viability of an idea before investing resources, plan within contexts of high uncertainty, coordinate multidisciplinary teams and stakeholders with differing interests, anticipate ethical and governance risks, and ultimately deploy and monitor solutions in production.

The course combines applied theory with real-world case studies, culminating in a final project where you will put everything you have learned into practice by designing and planning a complete AI project.

Module structure:

1. Fundamentals: what makes an AI project different
2. Discovery and viability: how to validate an idea before building
3. Planning and managing uncertainty: methodologies adapted to the probabilistic nature of AI
4. Teams and stakeholders: how to align technical and non-technical profiles
5. Risks, ethics and governance: frameworks for responsible development
6. Deployment, monitoring and final project: from prototype to production, with continuous tracking

Aimed at: project leaders, product managers, and technical professionals who want to manage AI initiatives with sound judgement and rigour.