Machine learning and artificial intelligence in agricultural systems
Description: The purpose of the course is to develop students' competencies in the development and implementation of intelligent systems for monitoring, forecasting and managing agrotechnological processes. The discipline is aimed at studying modern AI methods and their application in agriculture to increase the efficiency and sustainability of agricultural production. As a result of mastering the discipline, students acquire skills in working with machine learning algorithms, processing agricultural data, creating models for decision-making and applying AI technologies to solve practical problems in the agricultural sector.
Amount of credits: 8
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 30 |
| Practical works | |
| Laboratory works | 45 |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 45 |
| SAW (Student autonomous work) | 120 |
| Form of final control | Exam |
| Final assessment method |
Component: University component
Cycle: Profiling disciplines
