Artificial intelligence projects are not managed like traditional technology projects: uncertainty is higher, outcomes are not always predictable, and success depends as much on the data as on the people who interpret it. This course provides a practical roadmap for leading AI projects from start to finish, combining technical fundamentals, management tools, and a critical perspective on risks and ethics.
Throughout six modules, you will learn to identify what makes an AI project unique compared to a conventional one, assess the feasibility of an idea before investing resources, plan in highly uncertain environments, coordinate multidisciplinary teams and stakeholders with different interests, anticipate ethical and governance risks, and ultimately deploy and monitor solutions in production.
The course combines applied theory with real-world case studies and concludes with a final project in which 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 Feasibility : how to validate an idea before building
  3. Planning and Uncertainty Management : methodologies adapted to the probabilistic nature of AI
  4. Teams and Stakeholders : how to align technical and non-technical professionals
  5. Risks, Ethics, and Governance : frameworks for responsible development
  6. Deployment, Monitoring, and Final Project : from prototype to production, with continuous monitoring

Target Audience: project leaders, product managers, and technical professionals who want to manage AI initiatives with sound judgment and rigor.