The goal of this class is to teach non-mathematicians the fundamental concepts of
linear algebra. Linear algebra is foundational in all (applications of) mathematics and this class should provide a solid background for other quantitative classes (such as Statistics or Data Science), where linear algebra concepts are ubiquitous. Topics covered will include: vector spaces, matrices and linear maps, linear equations, scalar products, eigenvectors and eigenvalues.
Target group: PhD students in the life scientists with an interest in quantitative methods.
Prerequisites: Some high-School mathematics is helpful, but the class will be essentially self-contained.
Evaluation: Students will be graded based on their performance on the weekly exercise sheets.
Teaching format: Lectures and recitations, weekly exercise sheets.
ECTS: 3 Year: 2021
Track segment(s):
BIO-QUANT Biology - Quantitative and Computational Methods in Biology
NEU-QUANT Neuroscience - Quantitative and Computational Methods in Biology
Teacher(s):
Timothy Browning Florian Wilsch
Teaching assistant(s):
If you want to enroll to this course, please click: REGISTER
- Teacher: Grigory Ivanov