Minor AI (Advanced): Advanced Machine Learning and Deep Learning

Coordinated by: Michel Riveill, PR Université Côte d'Azur, Polytech, I3S

FORMAT

Hybrid

LOCATION

  • Campus SophiaTech
  • Campus Valrose
  • Remote courses

Prerequisites

CAPACITY

24 students

ABOUT THIS MINOR

This  minor is also open to students from the LIFE and SPECTRUM graduate schools.

Summary

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

PhD students for TP/TD supervision

Prerequisites
Bibliography
  • 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
  • QCM on the course (50%)
  • Student Project (50%)

SCHEDULE

This minor is not open this semester.