The academic content and curriculum of the Artificial Intelligence Operator Associate Degree Program aims to provide students with a wide range of theoretical knowledge and practical skills. The courses offered throughout the program range from the basics of artificial intelligence and related technologies to advanced topics.
First, the focus is on programming languages and software development skills. Students are taught widely used programming languages such as Python and R. These languages are chosen because they have strong libraries and community support in the fields of artificial intelligence and data science. Programming courses provide students with a solid foundation in basic algorithms and data structures.
The data structures and algorithms course teaches students how to organize data and write algorithms efficiently. These lessons form the basis of artificial intelligence applications. Students gain in-depth knowledge of various data structures (arrays, linked lists, stacks, queues, trees and graphs) and algorithms (sorting, searching, graph algorithms).
Artificial intelligence algorithms and machine learning courses provide students with an understanding of the basic concepts in this field. The machine learning course covers basic topics such as supervised learning, unsupervised learning and reinforcement learning. Students learn various machine learning methods such as regression, classification, clustering and deep learning. Deep learning focuses particularly on neural networks and their structure, functioning and applications.
Data mining and big data analytics courses teach students how to analyze large data sets and transform them into meaningful information. These courses cover data preprocessing, data visualization and various data mining techniques (pattern recognition, association rules, decision trees).
Robotic systems and sensor technologies courses teach students how robotic systems work and the components of these systems. These courses cover topics such as sensors, actuators and robotic control systems. Students learn how robots interact with their environment and how they manage these interactions.
The AI applications course shows students how AI is applied to real-world problems. These courses examine the use of AI in various sectors such as healthcare, finance, automotive, agriculture and game development. Through these courses, students develop various projects and have the opportunity to apply what they have learned in practice.
The AI ethics and social impacts course enables students to understand the ethical and societal dimensions of AI technologies. This course covers the impacts of AI on society, privacy issues, algorithmic justice, and the ethical use of AI systems.
In addition to providing students with theoretical knowledge, the program is supported by hands-on learning methods such as laboratory work and project-based learning. Students put their knowledge into practice by developing various projects and solving real-world problems. In this way, the artificial intelligence operator program prepares students for a successful career in the field, giving them both academic and practical skills.