Information on individual educational components (ECTS-Course descriptions) per semester

  
Degree programme:Bachelor Computer Science - Software and Information Engineering
Type of degree:FH Bachelor´s Degree Programme
 Full-time
 Summer Semester 2026
  

Course unit titleLinear Algebra and Calculus
Course unit code024717020101
Language of instructionGerman
Type of course unit (compulsory, optional)Compulsory
Semester when the course unit is deliveredSummer Semester 2026
Teaching hours per week6
Year of study2026
Level of course unit (e.g. first, second or third cycle)First Cycle (Bachelor)
Number of ECTS credits allocated6
Name of lecturer(s)Martin MÜLLER
Lisa SCHÖNENBERGER
Philipp WOHLGENANNT


Prerequisites and co-requisites

Discrete Mathematics

Course content

The "Linear Algebra" part includes the following chapters:

  • Vectors, matrices
  • Linear systems of equations
  • Linear mappings
  • Inverse matrices and determinants
  • Scalar product
  • Eigenvalues and eigenvectors
  • ev. principal axis transformation


The part "Analysis" includes the following chapters:

  • Sequences and series
  • Limits, convergence and continuity
  • The exponential function
  • Integration (definite, indefinite, improper)
  • Polynomials
  • Power and Taylor series
  • ev. Fourier-Analysis
Learning outcomes

Technical and Methodological Competence

In the first part of the course, students develop an understanding of the structures of linear space and linear mappings. Students know and understand various applications of linear mappings, such as computer graphics or solving linear equation systems.

In the second part, students develop a fundamental understanding of the mathematical concept of infinity, its application in calculating limits of sequences, series, and functions, and its connection with calculus. Furthermore, students know and understand applications of analysis, such as the use of polynomials and power series for approximating functions on the computer.

Through specifically selected learning and teaching methods, this course also contributes to the development of the following interdisciplinary competencies:

Social and Communicative Competence (S/K)

  • Reliability: Adhering to rules and agreements and completing one’s tasks with the promised quality


Self-Competence (S)

  • Learning Competence and Motivation: Ability and willingness to acquire new knowledge independently and learn from successes and failures
  • Adaptability: Ability to adapt to changing conditions and handle varying situations
  • Expressiveness: Ability to use clear and understandable language and appropriate word choice


Transfer Competence (T)

  • Analytical and Presentation/Communication Skills: Ability to grasp and organize extensive and complex relationships quickly, filter out the essentials, and present them in an understandable manner
  • Judgment and Problem-Solving Skills: Ability to assess situations and derive consequences and solutions
  • Organizational Skills: Ability to implement goals into work tasks and optimally use available resources
Planned learning activities and teaching methods

Lecture in front of the whole group, exercises in three groups on paper and on the computer. Individual feedback on homework.

Assessment methods and criteria

Written exam and evaluation of the exercises in the seminar.

For a positive grade, overall across all parts of the examination a minimum of 50% of the possible points must be achieved.

Comment

Non applicable

Recommended or required reading
Weitz, Edmund (2021): Konkrete Mathematik (nicht nur) für Informatiker: Mit vielen Grafiken und Algorithmen in Python. 2., überarb. u. erw. Aufl. 2021 Edition. Berlin: Springer Spektrum.
Mode of delivery (face-to-face, distance learning)

On-site course

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