Organic Agriculture Program

At the end of this course, the students;

1. Explain the fundamental concepts, relationships, and differences regarding artificial intelligence, machine learning, and deep learning.
2. Explain the operating principles of basic and advanced deep learning architectures based on artificial neural networks and apply them to appropriate problem types.
3. Perform data preparation, model creation, training, and testing processes using deep learning libraries.
4. Evaluate the performance of deep learning models, identify overfitting issues, and analyze and interpret the results of models developed for real-world problems.

• Lecture
• Questions/Answers
• Practice