Comment fonctionne l'IA?

Artificial intelligence is increasingly influencing how we study, work, communicate, make decisions and interact with technology and with each other. Yet understanding AI does not necessarily require a background in computer science, mathematics or programming.
This course provides a non-technical introduction to artificial intelligence, designed for students who have little or no prior experience with programming, computer science or advanced mathematics.
The course introduces the fundamental ideas behind AI and explains, in accessible terms, how modern AI systems work, what they can and cannot do, and how they are being used across different sectors of society.
Rather than focusing on programming or mathematical implementation, the course emphasizes conceptual understanding, critical thinking and practical awareness.

• Explain the fundamental concepts behind artificial intelligence in clear, non-technical terms.
• Distinguish between major approaches to AI, including rule-based systems, machine learning, deep learning and generative AI.
• Understand, at a conceptual level, how AI systems learn from data and produce predictions, forecasting, classifications or generated content.
• Explain basic concepts such as data, algorithms, models, training, inference, bias and evaluation.
• Identify common applications of AI in everyday life, business, science, law, education and public services.
• Recognize the main strengths and limitations of "current" AI systems.
• Understand the basic principles behind generative AI and large language models.
• Critically evaluate claims, demonstrations and media reports concerning AI.
• Identify important ethical, social, economic and legal questions raised by AI.
• Use AI tools responsibly and reflect critically on their appropriate use.

- Lectures introducing the key concepts.
- TP- Case studies drawn from real-world applications.
- Small-group discussions on social and ethical questions.
- Critical analysis exercises involving AI-generated content.

Course notes

• Université virtuelle

Additional information

The exact teaching location will be communicated at a later date.

Contacts

ihsane.gryech@ulb.be

Campus

Plaine, Solbosch

Method(s) of evaluation

• written examination
• Project
• Continuous assessment

written examination

Project

Continuous assessment

Mark calculation method (including weighting of intermediary marks)

• 50% written exam
• 30% project
• 20% in-class quizzes and homework

Language(s) of evaluation

• french
• (if applicable english )