== 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 [[Main/WS22_MaschinellesLernen1 | "Machine Learning 1" ]] lecture or the [[Main/SS23_LabCourse | "Lab Course Machine Learning" ]]  (this course is not a prerequisite). 




=== Dates ===

||'''Lecture:''' || MA 0.005 Starting 25.10 ||
||'''Tutorials:''' || offline/online mixed ||
|| '''ISIS '''|| [[https://isis.tu-berlin.de/course/view.php?id=33557|ID 33557]] ||
|| '''Responsible:''' || [[http://www.ml.tu-berlin.de/menue/members/klaus-robert_mueller/|Prof. Dr. Klaus-Robert Müller]] ||
|| '''Lecturer''' || Lorenz Vaitl / Dr. Ali Hashemi ||
|| '''Contact''' || cognitivealgorithms@ml.tu-berlin.de ||

=== 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):  [[Main/SS23_PyML| "Python for ML" ]], [[Main/SS23_JuML| "Julia for ML" ]], [[Main/SS23_MathML| "Mathematical Foundations for ML"]]  or a seminar: [[Main/SS23_KA_SE| "CA Seminar" ]]/ [[Main/WS23_MLDMS| "Machine Learning and Data Management Systems" ]]/ [[Main/SS23_MLQc |Quantum Chemistry for Machine Learning ]]/  [[Main/SS23_HOT |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.