The spring semester 2021 will take place online until further notice. Exceptions: Courses that can only be carried out with on-site presence. Please note the information provided by the lecturers.

Search result: Catalogue data in Autumn Semester 2018

Number Title Type ECTS Hours Lecturers Computer Science Bachelor First Year Examinations First Year Examination Block 1 401-0131-00L Linear Algebra O 7 credits 4V + 2U Ö. Imamoglu, O. Sorkine Hornung Abstract Introduction to linear algebra (vector spaces, linear transformations, matrices) , matrix decompositions (LU, QR, eigenvalue and singular value decomposition). Objective Die Lernziele sind:- die fundamentalen Konzepte der linearen Algebra gut zu verstehen und anwenden zu können- Anwendungen der linearen Algebra kennenzulernen Content Linear Algebra:Linear systems of equations, vectors and matrices, norms and scalar products, LU decomposition, vector spaces and linear transformations, least squares problems, QR decomposition, determinants, eigenvalues and eigenvectors, singular value decomposition, applications. Lecture notes Lecture notes "Linear Algebra" (by Gutknecht) in German, with English expressions for all technical terms. Prerequisites / Notice The relevant high school material is reviewed briefly at the beginning. 252-0025-00L Discrete Mathematics O 7 credits 4V + 2U U. Maurer Abstract Content: Mathematical reasoning and proofs, abstraction. Sets, relations (e.g. equivalence and order relations), functions, (un-)countability, number theory, algebra (groups, rings, fields, polynomials, subalgebras, morphisms), logic (propositional and predicate logic, proof calculi). Objective The primary goals of this course are (1) to introduce the most important concepts of discrete mathematics, (2) to understand and appreciate the role of abstraction and mathematical proofs, and (3) to discuss a number of applications, e.g. in cryptography, coding theory, and algorithm theory. Content See course description. Lecture notes available (in english) 252-0027-00L Introduction to Programming O 7 credits 4V + 2U T. Gross Abstract Introduction to fundamental concepts of modern programming and operational skills for developing high-quality programs, including large programs as in industry. The course introduces software engineering principles with an object-oriented approach based. Objective Many people can write programs. The "Introduction to Programming" course goes beyond that basic goal: it teaches the fundamental concepts and skills necessary to perform programming at a professional level. As a result of successfully completing the course, students master the fundamental control structures, data structures, reasoning patterns and programming language mechanisms characterizing modern programming, as well as the fundamental rules of producing high-quality software. They have the necessary programming background for later courses introducing programming skills in specialized application areas. Content Basics of object-oriented programming. Objects and classes. Pre- and postconditions, class invariants, Design by Contract. Fundamental control structures. Assignment and References. Basic hardware concepts. Fundamental data structures and algorithms. Recursion. Inheritance and interfaces, introduction to event-driven design and concurrent programming. Basic concepts of Software Engineering such as the software process, specification and documentation, reuse and quality assurance. Lecture notes The lecture slides are available for download on the course page. Literature See the course page for up-to-date information. Prerequisites / Notice There are no special prerequisites. Students are expected to enroll in the other courses offered to first-year students of computer science. 252-0026-00L Algorithms and Data Structures O 7 credits 3V + 2U + 1A M. Püschel, D. Steurer Abstract This course is about fundamental algorithm design paradigms, classic algorithmic problems, and data structures. The connection between algorithms and data structures is explained for geometric and graph problems. For this purpose, fundamental graph theoretic concepts are introduced. Objective An understanding of the design and analysis of fundamental algorithms and data structures. Content Es werden grundlegende Algorithmen und Datenstrukturen vorgestellt und analysiert. Dazu gehören auf der einen Seite Entwurfsmuster für Algorithmen, wie Induktion, divide-and-conquer, backtracking und dynamische Optimierung, ebenso wie klassische algorithmische Probleme, wie Suchen und Sortieren. Auf der anderen Seite werden Datenstrukturen für verschiedene Zwecke behandelt, darunter verkettete Listen, Hashtabellen, balancierte Suchbäume, verschiedene heaps und union-find-Strukturen. Weiterhin wird Adaptivität bei Datenstrukturen (wie etwa Splay-Bäume) und bei Algorithmen (wie etwa online-Algorithmen) beleuchtet. Das Zusammenspiel von Algorithmen und Datenstrukturen wird anhand von Geometrie- und Graphenproblemen illustriert. Hierfür werden grundlegende Konzepte der Graphentheorie eingeführt. Literature Th. Ottmann, P.Widmayer: Algorithmen und Datenstrukturen, Spektrum-Verlag, 5. Auflage, Heidelberg, Berlin, Oxford, 2011
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