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L'essentiel de l'intelligence artificielle

This module explores the essentials of Artificial Intelligence (AI), focusing on foundational concepts, algorithms, and applications. It covers the principles of machine learning, neural networks, natural language processing, and the ethical considerations surrounding AI deployment in various sectors.

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Bâtisseur de programmes d'études

Russell, Stuart J., and Peter Norvig. Artificial Intelligence: A Modern Approach. 4th ed. Pearson Series in Artificial Intelligence. Hoboken: Pearson, 2021.

Brachman, Ronald J., and Hector J. Levesque. Knowledge Representation and Reasoning. Amsterdam ; Boston: Morgan Kaufmann, 2004.

Marsland, Stephen. Machine Learning: An Algorithmic Perspective. Chapman & Hall/CRC Machine Learning & Pattern Recognition Series. Boca Raton: CRC Press, 2009.

Poole, David L., and Alan K. Mackworth. Artificial Intelligence: Foundations of Computational Agents. 2nd ed. Cambridge University Press, 2017.

https://doi.org/10.1017/9781108164085

Ghallab, Malik, Dana S. Nau, and Paolo Traverso. Automated Planning: Theory and Practice. 1st ed. Amsterdam ; Boston: Elsevier/Morgan Kaufmann, 2004.

Cawsey, Alison. The Essence of Artificial Intelligence. Essence of Computing Series. Harlow, England ; New York: Prentice Hall, 1998.

Russell, S. and P. Norvig. “Artificial intelligence: a modern approach.” Prentice Hall (3rd ed.), 2010.

Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep Learning. Adaptive Computation and Machine Learning. Cambridge, Massachusetts: The MIT Press, 2016.

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Russell, Stuart J., and Peter Norvig. Artificial Intelligence: A Modern Approach. 4th ed. Pearson Series in Artificial Intelligence. Hoboken: Pearson, 2021.

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