Review of Programming and Toolboxes, Packages, Modules; Iterative Linear Algebra Problems; Root Finding Programs; Recursive Functions and Algorithms; Optimisation Algorithms; Data Fitting and Interpolation; Extrapolation; Numerical Integration; Numerical Solutions of Differential Equations: IVPs and BVPs; Selected Topics (algorithms and coding in different fields).

For further information see the academic catalog: IAM592

#### Course Objectives

At the end of this course, the student will learn:

- how to solve linear algebra equations
- how to solve root finding problems in different fields
- recursive algorithms
- how to solve optimisation problems
- data analysis tools and data description
- numerical integration methods to calculate integrals involved in applied mathematics
- how to numerically solve initial as well as boundary value problems in differential equations

#### Course Learning Outcomes

Student, who passed the course satisfactorily will be able to:

- understand basic problems in applied mathematics
- be aware of possible ways to solve problems from different fields
- analise and interpret data from measurements or observations
- numerically solve basic optimisation problems
- numerically solve basic differential equations

#### Tentative (Weekly) Outline

- Review of Programming and Toolboxes, Packages, Modules
- Iterative Linear Algebra Problems
- Root Finding Problems
- Recursive Functions and Algorithms
- Optimisation Algorithms
- Data Fitting and Interpolation (and Extrapolation)
- Numerical Integration
- Numerical Solutions of Differential Equations: IVPs and BVPs
- Selected Topics: algorithms and coding distinctively from
- Actuarial Sciences
- Cryptography
- Financial Mathematics
- Scientific Computing

#### Course Textbook(s)

- Tobin A. Driscoll, Learning MATLAB, SIAM, 2009
- Tobias Oetiker, Hubert Partl, Irene Hyna and Elisabeth Schlegl, The Not So Short Introduction to LaTeX 2e, 2016 (https://tobi.oetiker.ch/lshort/lshort.pdf)