- Study programme and level: Interdisciplinary University Study Programme in Administrative Information Science - 1st Cycle
- 6 ECTS
- Course type: Elective
- Lectures: 45
- Tutorial: 30
- Individual work: 105
- Lecturer: Polona Oblak, PhD
1. Objectives and competences
- Ability of critical thinking.
- Developing skills in critical, analytical and synthetic thinking.
- A major part of the course is devoted to the understanding of the basic terms of mathematical analysis and linear algebra (i.e. convergence, functions, derivation, integration, vectors, matrices) and their application in computer science and other sciences.
- Numbers: real and complex numbers
- Vectors: vectors in real plane and in space;
- Matrices, systems of linear equations.
- Sequences: explicit and recursive sequence, limit;
- Functions: graph, composite, inverse function, elementary functions, continuity;
- Derivatives: definition, derivatives of elementary functions, rules of derivation, use of derivatives;
- Integrals: indefinite and definite integrals, techniques of integration, evaluation of definite integrals, use of integrals;
Exercise group time is in part devoted to the classical blackboard approach, the students solve computational problems with some help of TA. In part of the exercise groups the students individually solve computerized versions of problems using symbolic computation software.
A short homework is assigned every week and is compulsory. The purpose of the homework is to promote ongoing study and help students to understand the ideas and concepts of the course.
- Polona Oblak: Matematika, Ljubljana, 2014, matematika.fri.uni-lj.si/mat/matvsp.pdf.
- Gabrijel Tomšič, Bojan Orel, Neža Mramor: Matematika I; Ljubljana, Fakulteta za elektrotehniko in računalništvo.
- James Stewart: Calculus: early transcendentals (5th edition), Brooks/Cole - Thomson, cop. 2003.
- Neža Mramor Kosta, Borut Jurčič Zlobec: Zbirka nalog iz matematike I; Ljubljana, Fakulteta za elektrotehniko in računalništvo.
- R. Beezer: A First Course in Linear Algebra, linear.ups.edu.
4. Intended learning outcomes
Knowledge and understanding:
- Students should be able to demonstrate general knowledge of the basic linear algebra and mathematical analysis, and to understand mathematical formulas and models.
- Use of the basic methods of linear algebra and mathematical analysis in various disciplines of computer science.
- Learning mathematical language and rigor to understand and accurately describe phenomena, understanding the relationship between the theoretical model and its implementation in various areas of computer science.
- Use of the abstraction to enable students to solve problems that may come up in their field of specialization.
5. Learning and teaching methods
Lectures, exercise groups, homework assignments. The focus lies in continuous work with home assignments, using computer and computation software.
Type (examination, oral, coursework, project):
- Continuing (homework, midterm exams, project work) (50 %)
- Final (written and oral exam) (50 %)
Grading: 6-10 pass, 1-5 fail.