The CENG399 course is offered this semester as a service course exclusively for students of the Department of Food Engineering and the Department of Molecular Biology and Genetics. The course is designed as an applied introductory course to artificial intelligence, focusing on understanding concepts, methods, and applications rather than mathematical depth.

The primary objective of the course is to develop artificial intelligence literacy among students. In this context, students will learn the types of data specific to their fields, data preprocessing and analysis processes, and the fundamental principles of commonly used machine learning and deep learning approaches. Additionally, they are expected to understand how these methods can be applied to real problems within their disciplines, how to select appropriate models, how to determine suitable evaluation metrics, and how to interpret model outputs correctly.

Throughout the course, students will be expected to demonstrate analytical thinking and problem-solving skills. Prior programming knowledge is not required; however, students with programming experience may have an advantage. As part of the practical activities, tools such as Python, Jupyter Notebook, scikit-learn, WEKA, and Orange will be used.

Assessment will consist of one midterm exam, one final exam, and a project conducted throughout the semester. As part of the project, students will develop an application related to their field, prepare a report at the end of the term, and present their work.