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### [ 526GLWNALD13 ] Module Algorithms and Data Structures

Versionsauswahl
Es ist eine neuere Version 2022W dieses Fachs/Moduls im Curriculum Bachelor's programme Statistics and Data Science 2022W vorhanden.
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Workload Mode of examination Education level Study areas Responsible person Coordinating university
6 ECTS Accumulative module examination B1 - Bachelor's programme 1. year Business Informatics Wolfgang Narzt Johannes Kepler University Linz
Detailed information
Pre-requisites (*)Empfohlen: Modul Einführung in die Softwareentwicklung
Original study plan Bachelor's programme Business Informatics 2017W
Objectives Students are able to develop algorithms, work with abstract concepts and transform algorithms into programs. They both master the design of algorithms and the analysis of their structure and their behavior as well as the development of software based on these algorithms. They are aware of methods and concepts for systematic program development and of modeling complex data structures and they know algorithms for solving standard problems.
Subject basic concepts of algorithms, fundamental terms and forms of notation; structure and design of algorithms; structure and design of elementary and networked data structures; abstract data structures, abstract data types; recursion principle and recursive algorithms; complexity analysis of algorithms; algorithms with random numbers; sorting and search algorithms; algorithms or character strings; geometric and graph algorithms, exhaustion algorithms.
Further information The course will be taught in the form of a classical lecture. Students will receive materials that they complete in class in order to learn the development process for algorithms.

The lecture will be complemented by accompanying exercises. The exercises serve to add depth to the subject matter treated in the lecture and afford students the opportunity to test whether they can actually apply the knowledge from the lecture. Normally nine exercises are distributed. Sample/Selected model solutions are discussed during the exercise periods. Additional exercises are prepared for selected topics to be solved collectively. In addition, students have the opportunity to reflect on topics from the lecture and to discuss unsolved problems with trainers. Initial evaluation is done by student assistants and final evaluation by the lecturer.

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