inf962 - Fundamental Competencies in Computing Science III: Algorithms and Computational Problem Solving

inf962 - Fundamental Competencies in Computing Science III: Algorithms and Computational Problem Solving

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Module label Fundamental Competencies in Computing Science III: Algorithms and Computational Problem Solving
Modulkürzel inf962
Credit points 6.0 KP
Workload 180 h
Institute directory Department of Computing Science
Verwendbarkeit des Moduls
  • Master Applied Economics and Data Science (Master) >
  • Master's Programme Engineering of Socio-Technical Systems (Master) > Fundamentals/Foundations
  • Master's Programme Environmental Modelling (Master) >
Zuständige Personen
  • Vogel-Sonnenschein, Ute (module responsibility)
  • Lehrenden, Die im Modul (Prüfungsberechtigt)
Prerequisites
No specific knowledge is required to take part in this module.
Skills to be acquired in this module
Graduates of the module have acquired a deeper understanding of basic theories and techniques in computer science and can classify problems that arise. This enables students to structure and model simple tasks from their subject area using computer science, to design approaches to solutions and to estimate the effort required to solve them. They have a basic understanding of the design and use of relational databases.

This course provides students with fundamental computational problem-solving skills necessary to complete subsequent courses in computer science.

Professional competences
The students
  • name the basic concepts of von Neumann's computer architecture,
  • describe concepts of the computational representation of information and their limits,
  • use basic data structures and algorithms and reason about their complexity,
  • model simple problems with formal concepts such as automata and formal languages,
  • design simple relational databases and identify the advantages of database-based storage.

Methodological competences
The students
  • analyze problems from their area of application,
  • design appropriate solutions for simple problems using the Python programming language and estimate the effort required to execute them,
  • design simple object-oriented models
  • use a simple IDE and implement scripts in Python,
  • discuss alternative computational representations of data and problems and draw informed conclusions from them
Social competences
The students
  • present and discuss their solutions in an interdisciplinary team,
  • develop solutions to simple problems cooperatively in a team.

Self-competences
The students
  • critically reflect on fundamental design decisions in algorithms and data structures,
  • deepen their time management skills.
Module contents
  • von Neumann computer architecture,
  • tasks of operating systems
  • computer representation of information,
  • formal languages, grammar and automata,
  • basic data structures,
  • algorithms and complexity,
  • programming simple object-oriented solutions in Python
  • basic concepts of SQL-based databases
Literaturempfehlungen
Links
Language of instruction English
Duration (semesters) 1 Semester
Module frequency every winter semester
Module capacity unlimited
Reference text
This module provides students with non-computer science backgrounds with the computational problem-solving skills necessary to complete subsequent computer science courses. It is not intended for students with a computer science background.
Teaching/Learning method 1VL + 1Ü
Previous knowledge none
Form of instruction Comment SWS Frequency Workload of compulsory attendance
Lecture 3 WiSe 42
Exercises 1 WiSe 14
Präsenzzeit Modul insgesamt 56 h
Examination Prüfungszeiten Type of examination
Final exam of module
  • The exam takes place in the first three weeks after the end of the event period.
  • The re-exam takes place in the last three weeks before the start of the next event period.
  • Practical exercises and exams
    or
  • Practical exercises and oral examination (with fewer than 20 participants)

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