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e-KUL
WEB S4A
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Computer modeling and simulations (classes) (ćwiczenia) - 2019/2020
Course description
General information
Lecturer:
dr hab. Aliaksandr Chychuryn prof. KUL
Organising unit:
Faculty of Science and Health - Instytut Matematyki, Informatyki i Architektury Krajobrazu
Number of hours (week/semester):
2/30
Language of instruction:
English
Course objective
1. The student understands what is computer modeling and simulation;
2. The student knows the basic rules for applying the capabilities of Mathematica and Matlab;
3. The student knows the basic capabilities of the environment WebMathematica
Prerequisites
INTRODUCTORY COURSES AND PREREQUISITES:
1. Knowledge of basis for computing;
2. Programming skills;
3. The ability to search for information on the Internet;
4. Knowledge of basis for mathematical analysis and algebra in the first year in education of computer science
Learning outcomes
KNOWLEDGE
After completing the course, students can:
W1 define the concepts of modeling and simulation K_W01 K_W02
W2 analyze approaches to solving of differential and algebraic equations in the Mathematica / Matlab program K_W01 K_W02
W3 formulate the differences between various methods of visualization and animation programs available K_W01 K_W02
W4 select online sources of knowledge, which can be traced to ready-made examples of models in various fields prepared in Mathematica code (WebMathematica 3.3) K_W01 K_W06
W5 know basic applications of programs MatLab, Scilab and WolframAlpha K_W05
SKILLS
After completing the course, students can:
S1 use different data collections available in Mathematica and Matlab programs K_U06 K_U11
S2 can create visualizations of known models K_U06 K_U11
S3 is able to create simulations of known models K_U06
S4 can use MatLab, Scilab and WolframAlpha programs K_U03
S5 can solve simple models using the MatLab, Scilab and Mathematica programs, containing differential equations with initial conditions K_U17
SOCIAL COMPETENCE
SC 1 formulate opinions about selected models K_K01
Teaching method
laboratory, multimedia presentation, workshop
Course content description
COURSE CONTENTS:
1. Introduction to Matlab; 2
2. WolframAlpha Basics; 2
3 i 4. Linear algebra. Solving linear systems in Matlab; 4
5. Linear algebra. Numerical and symbolic calculations in WolframAlpha; 2
6. Numerical and symbolic calculations in Matlab/Scilab; 2
7 i 8. 2D/3D visualization in Matlab; 4
9 i 10. Vizualization and animation in Matlab. Elements of programming; 4
11. 2D/3D visualization in WolframAlpha; 2
12. Vizualization and animation in WolframAlpha. Elements of programming; 2
13. Exam. 2
14 i 15. CDF-Player. Demonstrations projects (student presentations). WebMathematica; 4
Total hours: 30
Forms of assessment
Passing classes - 1 colloquium (80%), 1 demonstration project (20%)
Oral exam
Lecture assesment = assesment of exercise + (-) oral exam if the student obtains a higher (lower) grade.
W1 - exam, colloquium, test, preparation for classes, activity in classes
W2 - exam, colloquium, test, preparation for classes, activity in classes
W3 - exam, colloquium, activity in classes
W4 - exam, colloquium, test, preparation for classes, activity in classes
W5 - exam, colloquium, test, preparation for classes, activity in classes
U1 - exam, colloquium, test, preparation for classes, activity in classes
U2 - exam, colloquium, test, preparation for classes, activity in classes
U3 - preparation for classes, activity in classes
U4 - exam, colloquium, test, preparation for classes, activity in classes
U5 - exam, colloquium, preparation for classes, activity in classes
K1 - preparation for classes, activity in classes
HOURLY EQUIVALENTS ECTS
Hours implemented within the program of studies
Lecture 30
Classes 30
Total number of hours 60
Own work
Preparation for classes 20
Studying literature 15
Preparation for colloquium and test (exam) 35
Total number of hours 70
Total number of ECTS credits for module 5
Required reading list
REQUIRED READING:
1. Edwards C. Henry, Penney David E. Differential Equations and Boundary Value Problems: Computing and Modeling. - Pearson Prentice Hall. 2008. - 816 p.
2. Giordano Frank R., Fox William P., Horton Steven B. A First Course in Mathematical Modeling. - Brooks/Cole, Boston. 2014. - 676 p.
3. Wagon S. Mathematica in Action: Problem Solving Through Visualization and Computation, Third Edition. - New York: Springer-Verlag, 2010. - 680 p.
4. Pratap Rudra, MatLab 7 for scientists and engineers. Warszawa: PWN, 2010.
RECOMMENDED READING:
1. Grzymkowski R., Kapusta A., Kuboszek T., Slota D. Mathematica 6. - Gliwice: Wydawnictwo Pracowni Komputerowej Jacka Skalmierskiego, 2008. - 718 p.
2. Ruskeepää, Heikki. Mathematica Navigator: Mathematics, Statistics, and Graphics. - Burlington, San Diego, London: Elsevier, - 3rd ed. 2009. - 1112 p.
OTHER LEARNING RESOURCES
www.wolframalpha.com
www.demonstrations.wolfram.com
www.wolfram.com/learningcenter/tutorialcollection
www.virtualregion.kul.pl
Field of study: Informatics
Course listing in the Schedule of Courses:
Year/semester:
Year II - Semester 3
Number of ECTS credits: 0
Form of assessment: Grade
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