Master of Science in Discrete Mathematics and its Applications

2020/2021 call is open!

http://www.math.uniri.hr/en/component/content/article.html?layout=edit&id=772

Description

Discrete mathematics is the branch of mathematics dealing with discrete mathematical structures, i.e. mathematical structures over countable sets (finite sets or sets with the same cardinality as the natural numbers). Topics in discrete mathematics, among others, include combinatorics, graph theory, coding theory, and cryptography.

Career opportunities

The completion of this kind of study provides a good basis for the possible development of a scientific career in the field of science and engineering, but it also provides potential employment in various areas, at the positions which require an algorithmic way of thinking and the ability to analyze data. The knowledge gained in this study program is highly applicable in the economy; graph theory has broad application, from telecommunications to the design of road networks, coding theory and cryptography are used daily in communication. Since there will be more and more jobs related to ICT technologies and data protection, the need for this profile of personnel will increase. The optimization is very purposeful in various business processes, while the design and analysis of experiments are necessary for carrying out of an experiment, from the production of new drugs to machine testing. Also, the knowledge in the field of experimental design is very applicable in examining the characteristics of the finished products and we expect the labor market to demonstrate the need for our graduates.

Required educational level for enrollment:

• Bachelor’s degree in Mathematics or equivalent qualification in Mathematics

Curriculum - 120 ECTS

Semester 1

• Vector spaces 1
• Measure and Integral
• Algebra 1
• Linear programming
• Graph theory

Semester 2

• Statistics
• Algebra 2
• Probability theory
• Artificial intelligence
• Coding theory and cryptography

Semester 3

• Permutation groups
• Number theory
• Introduction to design theory
• Design and analysis of experiments
• Nonlinear optimization

Semester 4

• Seminar of M.Sc. thesis
• Combinatorial optimization
• Machine learning
• Optimization techniques for data mining
• Optimization methods in finance
• Graduation