Description
Introduction a la intelligence artificial
This comprehensive course explores formal reasoning in artificial intelligence through two main approaches: logic (deductive reasoning) and probability theory (for handling uncertainty). Students will master three logical systems and three probabilistic graphical models, gaining a solid foundation in both theoretical concepts and practical applications.
Skills you’ll gain
This course includes
| ⏱️20 Hours Of Self-paced video lessons |
| 🌱Intermediate Level |
| 📜Completion Certificate awarded on course completion |
What you’ll learn
- Understand and apply propositional logic concepts including syntax, semantics and inference
- Implement the DPLL algorithm for logical reasoning
- Master temporal logic for model verification in AI systems
- Understand predicate logic as a foundation for various AI techniques
- Apply Bayesian networks for probabilistic reasoning under uncertainty
- Implement and utilize Markov chains for sequential data modeling
- Develop Markov Decision Process models for decision-making in uncertain environments
- Apply game theory principles to multi-agent reasoning scenarios
Top companies offer this course to their employees
Top companies provide this course to enhance their employees’ skills, ensuring they excel in handling complex projects and drive organizational success.
Get a Completion Certificate
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