Number of hours
- Lectures 15.0
- Projects -
- Tutorials -
- Internship -
- Laboratory works 6.0
- Written tests -
ECTS
ECTS 3.5
Goal(s)
Investigate the main models of Artificial Intelligence. The courses and practical work allow students to discover and create AI models by themselves, starting from elementary components (such as the formal neuron) towards the most complex models (such as deep neural networks). Unlike black-box approach, the course aims at understanding in detail how the models studied work.
Laurent LEFEVRE
Content(s)
- The history of AI and its various models
- neural networks: from formal neuron to deep learning
- unsupervised networks and self-organizing maps
- reinforcement learning
- robotics and developmental learning
A preliminary experience (basic knowledge) in programming (Java and Python)
The evaluation includes two labs (50%) and a final exam (50%).
TP (lab): two sessions with evaluation of in-session work and written report
E1: session 1 individual exam (practical and theoretical)
E2: session 2 individual exam (practical and theoretical)
DM: (in case of confinment) individual homework with report and online oral exam
The exam is given in english only
The course exists in the following branches:
- Curriculum - Network and computer science - Semester 9 (this course is given in english only )
Course ID : 5AMCS529
Course language(s):
The course is attached to the following structures:
- Team Computer Science
You can find this course among all other courses.