Artificial intelligence applications are used in very different areas to solve different kinds of problems. Different artificial intelligence approaches are applied, whereby it must be assessed in each case which method is best suited for which problems.
The module aims to acquire methodological, analytical, and technical competencies to use artificial intelligence according to needs and application scenarios. For this purpose, some approaches to machine learning will be discussed methodically first. In particular, knowledge of the distinction between supervised and unsupervised methods and overfitting, regression, and classification will be acquired, which serve as canonical foundations for artificial intelligence methods. Based on this, methods of neural networks, perceptron models, and activation functions will be applied. The module enables the practical application of artificial intelligence methods in different scenarios and the critical analysis of these methods.