Coordinated by: Michel Riveill, PR Université Côte d'Azur, Polytech, I3S
FORMAT
Hybrid
LOCATION
- Campus SophiaTech
- Campus Valrose
- Remote courses
Prerequisites
- Scientific Bachelor
- Python programming
- Prerequisites and main concepts of Minor AI Introduction
CAPACITY
24 students
ABOUT THIS MINOR
This minor is also open to students from the LIFE and SPECTRUM graduate schools.
- Summary
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LEARNING OUTCOMES
- Know the principles of Deep Learning (neural network)
- Know how to build models based on neural networks to process structured data, images or text
- Lecturers
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- Diane Lingrand (MC Université Côte d'Azur, Polytech, I3S)
- Michel Riveill (PR Université Côte d'Azur, Polytech, I3S)
PhD students for TP/TD supervision
- Prerequisites
- Bibliography
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- Statistics and Machine Learning in Python. Edouard Duchesnay, Tommy Löfstedt (presents Python language for machine learning)
- Python Machine Learning. Sebastian Raschka
- Hands-on machine learning with Scikit-Learn and TensorFlow: concepts, tools, and techniques to build intelligent. A. Géron. O’Reilly (practical)
- Data science : fondamentaux et études de cas: Machine learning avec Python et R. M. Lutz, E. Biernat. Editions Eyrolles (In French, introduction level but requires some maths background
- Evaluation
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- QCM on the course (50%)
- Student Project (50%)
SCHEDULE
This minor is not open this semester.