The students remember and understand the basic tasks and method of mathematical algorithms and their praktical appliastion, are able to use mathematical programming tools, are able to apply, analyze and implement mathematical algorithms, are able to document and present mathematical algorithms.
The focus of the Advanced Computerlab Statistical Learning is on well-known machine learning methods. These are mainly considered from the perspective of mathematical statistics. For presented structured and unstructured data, students are taught how to find suitable solutions, how to implement them, e.g. in the statistical software R, and how to interpret the results. Advantages and disadvantages of the methods used as well as the underlying model assumptions are discussed from a probabilistic or statistical point of view. Students have the opportunity to apply their knowledge of probability theory and mathematical statistics acquired in previous courses. One focus of the course is the independent implementation of machine learning models using frameworks such as TensorFlow, mlr3, Keras, among others.
Code | 1294074 + 1294075 |
---|---|
Degree programme(s) | Mathematics in Finance and Industry, Data Science, Mathematics |
Lecturer(s) | Prof. Dr. Jens-Peter Kreiß, Prof. Dr. Nicole Mücke, Prof. Dr. Benedikt Jahnel |
Type of course | Lecture and exercise course |
Semester | Winter semester |
Language of instruction | English |
Level of study | Master |
ECTS credits | 5 |
Contact person | mathe-studium@tu-braunschweig.de |
Vacancies of TU Braunschweig
Career Service' Job Exchange
Merchandising
Term Dates
Courses
Degree Programmes
Information for Freshman
TUCard
Technische Universität Braunschweig
Universitätsplatz 2
38106 Braunschweig
P. O. Box: 38092 Braunschweig
GERMANY
Phone: +49 (0) 531 391-0