3. Competent

•AI Knowledge: Understands artificial intelligence methods in detail, knows the logic of the algorithms and can use them in practice.

•Technical Skills: Proficient in languages ​​such as Python, R, able to develop models of moderate complexity using TensorFlow or PyTorch.

•Problem Solving: Analyzes real-world problems, chooses algorithms logically, and can produce solutions.

•Data Literacy: Works comfortably with various data sources and has data pre-processing and advanced data analysis competencies.

•AI Ethics: Masters ethical practices and has the ability to evaluate biases and fairness in the model.

•Communication and Collaboration: Conveys technical knowledge in an understandable manner and actively participates in teamwork.

•Application and Industry Knowledge: Identifies problems in specific industries and can apply them.

•Continuous Learning: Follows current developments and acquires new skills regularly.