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(in Polish) Discrete Mathematics

General data

Course ID:	420-IS1-1MDY-ENG
Erasmus code / ISCED:	11.101 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0541) Mathematics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	(unknown)
Name in Polish:	Discrete Mathematics
Organizational unit:	Institute of Computer Science
Course groups:
ECTS credit allocation (and other scores):	5.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	English
Type of course:	obligatory courses
Requirements:	Elements of Logic and Set Theory 420-IS1-1PLTM Linear Algebra with Analytic Geometry 420-IS1-1ALG Mathematical Analysis 1 420-IS1-1AM1
Prerequisites:	Elements of Logic and Set Theory 420-IS1-1PLTM Linear Algebra with Analytic Geometry 420-IS1-1ALG Mathematical Analysis 1 420-IS1-1AM1
Mode:	(in Polish) w sali
Short description:	Course objectives: To learn basic methods and tools of combinatorics, graph theory, and number theory and how one can use them in solving of computational problems.
Full description:	Course profile: General Academic Form of study: Full-time studies Course type: Basic Field of science: natural sciences, Discipline of science: computer science Year/semester of study: 1 / 2 Prerequisites (sequential system of courses and exams): Items introducing: Elements of Logic and Set Theory, Linear Algebra with Analytic Geometry, Mathematical Analysis 1, ECTS credits: 5 Balance of student workload: Class attendance: - lecture 30h - exercise classes 30h Course preparation: - lecture 5h - exercise classes 20h Literature familiarization: 10h Preparation for tests: 20h Preparation for the exam: 20h Test duration: 2h Exam duration: 2h The total number of hours of exams and tests: 4h Individual consultation with the teacher: 2h Student workload: - that requires direct interaction with the teacher: 66h, 2 ECTS - that does not require direct interaction with the teacher: 75h, 3 ECTS
Bibliography:	Kenneth H. Rosen, Handbook of discrete and combinatorial mathematics (Discrete mathematics and its applications - 1st Edition), CRC Press. Ralph P. Grimaldi, Discrete and combinatorial mathematics: An applied introduction, 2nd Edition. Kenneth A. Ross, Charles R.B. Wright, Discrete mathematics, 5th Edition
Learning outcomes:	Learning outcomes: The student knows mathematical tools necessary to construct and analyse algorithms. KP6_WG3 The student knows basic notions of combinatorics, graph theory, and number theory. KP6_WG1 The student can use the concepts and properties of functions, sequences and series to solve simple problems of a recursive nature. KA6_UW2 The students can apply combinatorics, recurrence, and mathematical induction to solve simple computational problems. KP6_UW4 The student can apply the breath-first search method to searching of the shortest path in a weighed graph. KP6_UW6 The student is able to independently implement an algorithm using the selected programming language KA6_UW8 The student understands the need of continual learning. KP6_UU1
Assessment methods and assessment criteria:	Form of assessment: class tests and the final exam (written or oral).

Classes in period "Academic year 2022/2023" (past)

Time span:	2022-10-01 - 2023-06-30	Selected timetable range: weekly course term Navigate to timetable
Type of class:	Class, 30 hours more information Lecture, 30 hours more information
Coordinators:	Karol Pąk
Group instructors:	(unknown)
Students list:	(inaccessible to you)
Examination:	Course - Examination Class - Grading

Course descriptions are protected by copyright.
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