Learning outcomes

Mastering basics of probability theory (probability, probability axioms, conditional probability, probability density function, cumulative distribution function, expectation, variance, discrete random variable, continuous random variable) and statistics (statistical experiment, descriptive statistics, inference statistics). Ability to calculate with complex numbers and matrices (also determinant, eigenvalues and eigenvectors), and define extremum values of a given function. Cabapility to analyse and solve differential equations.

Contents

Essential math and CS methods with applications to bioinformatics. The course content includes probability theory, statistics, complex numbers, matrices, ordinary differential equations, extremum values.

Teaching methods

Teaching method	Contact	Online
Lectures	10 h	0 h
Exercises	10 h	0 h

Teaching language

English

Evaluation

Numeric 1-5.

Recommended year of study

1. year autumn

Study materials

Lecture notes.

Further information

Organization responsible: Turku DIT

Belongs to following study modules