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Integrated Lecture "Cognitive Algorithms"

Computer programs can learn useful cognitive skills. This integrated lecture tries to communicate an intuitive understanding of elementary concepts in machine learning and their application on real data with a special focus on methods that are simple to implement. For a more advanced treatment we recommend the "Machine Learning 1" lecture or the "Lab Course Machine Learning" (this course is not a prerequisite).

Dates

Lectures/Tutorials

Lectures and tutorials take place every other week respectively. Lectures and tutorials will be held in person. Tutorials will also be offered via Zoom.

Prerequisites

The following prerequisites are helpful for taking the course:

• Basic knowledge in linear algebra and calculus
• Basic programming knowledge, programming in Python

• To participate in the exam you first need to pass the elective course

Credits

The integrated lecture is the compulsory part of the B.Sc. module "Kognitive Algorithmen" in Computer Science. This "Kognitive Algorithmen" module is a 6 ECTS/SP module, and consists of

• The compulsory integrated lecture (2 SWS / 3 SP / 3 ECTS), and

• An elective (2 SWS / 3 SP / 3 ECTS): "Python for ML", "Julia for ML", "Mathematical Foundations for ML" or a seminar: "CA Seminar"/ "Machine Learning and Data Management Systems"/ Quantum Chemistry for Machine Learning/ Hot Topics in Machine Learning for a more in-depth treatment of selected applications.

The grade will be determined in a written exam at the end of the semester. The grades of the elective will not count towards the grade of the entire module.