(MLA) Courses

The Machine Learning professionals we train are keen to apply state of the art algorithms to industry and social challenges. To provide them with the necessary tools, students will be given both the scientific foundations to deeply understand the main ML concepts, and the technical preparation to implement new algorithms in the real world. 

Fundamental Courses
Elements of linear algebra for AI Cecconi
Fundamentals of statistics for AI with R software Paolucci/Cecconi
Python Programming for AI (including Git, NumPy, Pandas, MatPlotLib)  Mannella
Elements of Numerical Optimization for AI Di Lorenzo
Elements of Machine Learning (including SciKitLearn) Scardapane
Fundamentals of Reinforcement Learning Santucci
School/project monitoring and soft-skills Baldassarre/Caligiore
Specialistic Courses
Deep Neural Networks: theory and technologies (Tensor Flow) Totaro/Valigi
Machine-learning project management and deployment (including cloud resources for deployment and training) Valigi
Visual Perception and Spatial Computing Freda
Systems Neuroscience Ferraina
Focussed Courses
Deep Reinforcement Learning Di Palo
Bringing ML in businesses  Mauro
AI Planning and Scheduling and some applications in Robotics Rasconi/Oddi
Commercial and serious games Miglino/Schembri
Introduction to Physical Computing with Arduino Sperati
Towards Designing Emotional Socially Assistive Robots Özcan
Evolutionary robotics Nolfi
Swarm Robotics Trianni
Project Management and Funding Sources Fantini