# 13912 - Coding Theory Modulübersicht

 Module Number: 13912 Module Title: Coding Theory Datenkodierung Department: Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology Responsible Staff Member: Prof. Dr. rer. nat. Averkov, Gennadiy Language of Teaching / Examination: English Duration: 1 semester Frequency of Offer: On special announcement Credits: 6 Learning Outcome: After successfully completing the module, students will know and understand the problems and basics of data coding. They can transfer known facts and procedures of linear algebra to this application field and have learned further concepts of algebra. They know linear codes and understand the meaning of the parameters. They know simple decoding algorithms, can apply them and show their correctness. Contents: Basics of coding theoryTheory of linear codesExamples of linear codes, in particular, Reed-Solomon codesGeneral and specific decoding algorithmsSimple Goppa codes Recommended Prerequisites: Knowledge of the content of the modules 11101: Lineare Algebra und analytische Geometrie I or 11112: Mathematik IT-1 (Diskrete Mathematik), and11113: Mathematik IT-2 (Lineare Algebra) Mandatory Prerequisites: None Forms of Teaching and Proportion: Lecture / 3 Hours per Week per Semester Exercise / 1 Hours per Week per Semester Self organised studies / 120 Hours Teaching Materials and Literature: van Lint, J., van der Geer, G., Introduction to Coding Theory and Algebraic GeometryJ.I. Hall, Notes on Coding TheoryWillems, Wolfgang, Codierungstheorie und Kryptographie Module Examination: Final Module Examination (MAP) Assessment Mode for Module Examination: Final module examination:Written examination, 90 min. OROral examination, 30 - 45 min. (with small number of participants) In the first lecture it will introduced, if the examination will organized in written or oral form. Evaluation of Module Examination: Performance Verification – graded Limited Number of Participants: None Part of the Study Programme: Master (research-oriented) / Angewandte Mathematik / PO 2019 Master (research-oriented) / Artificial Intelligence / PO 2022 Bachelor (research-oriented) / Informatik / PO 2008 Master (research-oriented) / Informatik / PO 2008 Bachelor (research-oriented) / Mathematik / PO 2023 Bachelor (research-oriented) - Co-Op Programme with Practical Placement / Mathematik - dual / PO 2023 Bachelor (research-oriented) / Wirtschaftsmathematik / PO 2023 Bachelor (research-oriented) - Co-Op Programme with Practical Placement / Wirtschaftsmathematik - dual / PO 2023 Remarks: Study programme Angewandte Mathematik M.Sc.: Compulsory elective module in complex „Analysis / Algebra / Kombinatorik“Study programme Mathematik B.Sc.: Compulsory elective module in complex „Vertiefung“, in limited extend Study programme Wirtschaftsmathematik B.Sc.: Compulsory elective module in complex „Vertiefung“, in limited extendStudy programme Artificial Intelligence M.Sc.: Compulsory elective module in complex  „Knowledge Acquisition, Representation, and Processing“Study programme Informatik B.Sc.: Compulsory elective module in „Praktische Mathematik" or in field of application „Mathematics"Study programme Informatik M.Sc.: Compulsory elective module in „Mathematik" or in field of application „Mathematik" Module Components: Lecture Coding Theory, with integrated exerciseRelated examination Components to be offered in the Current Semester: 130281 Examination Coding Theory (Wiederholung)