Completed the course Računalniški praktikum.
Computer science
2020/2021
Programme:
Physics, First Cycle
Orientation:
Meteorology
Year:
2 year
Semester:
first or second
Kind:
mandatory
ECTS:
3
Course director:
Hours per week – 1. or 2. semester:
Lectures
2
Seminar
0
Tutorial
1
Lab
0
Content (Syllabus outline)
Basics of a higher-level programming language: If the language is object-oriented: control structures (loops and conditionals), classes and objects, methods, subclasses and inheritance. Foundations of data structures and algorithms: Time and space computational complexity, basic data structures, sorting algorithms, divide an conquer, dynamic programming, backtracking. Data processing and visualization: regular expressions and their use in data processing, graphical representation of numerical data. Optional content: basic notions in database theory, basics of SQL.
Readings
1.Priročnik za programski jezik.
2.T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms. 2nd ed., MIT Press, Cambridge, 2001.
3.J. Kozak, Podatkovne strukture in algoritm., DMFA-Založništvo, Ljubljana, 1997.
4.T. Mohorič, Podatkovne baze. 2. dopolnjena izdaja, BI-TIM, Ljubljana, 2002.
5.Priročnik za delo s podatkovno bazo.
Objectives and competences
The course introduces the student to fundamentals of structured programming, data structures, algorithms, and methods for processing and vizualization of data.
Intended learning outcomes
Knowledge and understanding: Basic training in programming and algorithmic approach to problem solving.
Application: The knowledge attained in the course enables the student to solve complex and large computational and other problems with the help of a computer.
Reflection: The realization that the efficiency of solution depends critically on how data is organized and represented as a data structure, and what algorithms are used to tackle the problem.
Transferable skills: Programming skills acquired in the course can be used to solve problems in other courses, especially those whose solutions are obtained through complex computational processes and simulations of physical systems.
Learning and teaching methods
Lectures, seminars, exercises and homeworks.
Assessment
Homeworks, 2 midterm exams or a written exam
oral exam
6-10 (passing) in 5 (failing) , following the statute of UL.
Lecturer's references
HAJDINJAK, Melita, BAUER, Andrej. Similarity-based relations in Datalog programs. Int. j. uncertain. fuzziness knowl.-based syst., Oct. 2012, vol. 20, no. 5, str. 673-700 [COBISS-SI-ID 9428308] BAUER, Andrej, KAVKLER, Iztok. A constructive theory of continuous domains suitable for implementation. Ann. pure appl. Logic. [Print ed.], str. 251-267. http:/dx.doi.org/10.1016/j.apal.2008.09.025 [COBISS-SI-ID 15329625] BAUER, Andrej, STONE, Christopher A. RZ: a tool for bringing constructive and computable mathematics closer to programming practice. Lect. notes comput. sci., str. 28-42.http:/www.springerlink.com/content/l745202373001555/fulltext.pdf [COBISS-SI-ID 14631769] AWODEY, Steve, BAUER, Andrej. Propositions as [Types]. J. log. comput. (Print), 2004, vol. 14, no. 4, str. 447-471. http:/logcom.oupjournals.org/content/vol14/issue4/index.dtl [COBISS-SI-ID13374809] BAUER, Andrej, PETKOVŠEK, Marko. Multibasic and mixed hypergeometric Gosper-type algorithms. J. symb. comput., 1999, let. 28, št. 4-5, str. 711-736 [COBISS-SI-ID 9210969]
