Чему вы научитесь
This course consists of lectures and laboratory work assignments. It focuses on key methods of Artificial intelligence and Machine learning. It provides hands-on experience and promotes a ‘learn-by-doing” approach.
Our course includes:
•Brief theoretical explanation focused on
algorithms
•Functional computer models
•Source
code with comments for all covered models
Course Section:
•The
history
of AI & ML
•Simulated
annealing
method
•Perceptron
learning
•Hopfield
Networks
•Classification
using Kohonen
Networks
•Self-Organizing
Maps, SOM
•Genetic
algorithms
•Reinforcement
learning
•Deep
Learning. Important trends. The Python Deep Learning library «Keras».
Modern high-level neural networks with a focus on enabling fast experimentation
О курсе
Goal of course: learn the basic AI and ML methods and their application in practice
Tasks:
to study the history AI and ML development;
to learn the basic terms and the main methods of AI and ML; to investigate the possibility of applying AI and ML
Для кого этот курс
Masters
Преподаватели курса
Нагрузка
48 academic hours