Introduction to Computational Mathematics (MAE742A): Διαφορά μεταξύ των αναθεωρήσεων
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=== General === | === General === | ||
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See the official [https://service.eudoxus.gr/public/departments#20 Eudoxus site] or the [https://cloud.math.uoi.gr/index.php/s/62t8WPCwEXJK7oL local repository] of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus: | See the official [https://service.eudoxus.gr/public/departments#20 Eudoxus site] or the [https://cloud.math.uoi.gr/index.php/s/62t8WPCwEXJK7oL local repository] of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus: | ||
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Τελευταία αναθεώρηση της 12:36, 15 Ιουνίου 2023
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General
School |
School of Science |
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Academic Unit |
Department of Mathematics |
Level of Studies |
Undergraduate |
Course Code |
MAE742A |
Semester |
7 |
Course Title |
Introduction to Computational Mathematics |
Independent Teaching Activities |
Lectures (Weekly Teaching Hours: 3, Credits: 6) |
Course Type |
Special Background |
Prerequisite Courses | - |
Language of Instruction and Examinations |
Greek |
Is the Course Offered to Erasmus Students |
Yes (in English) |
Course Website (URL) | See eCourse, the Learning Management System maintained by the University of Ioannina. |
Learning Outcomes
Learning outcomes |
Science is based on two major pillars, both theoretical and experimental. However, over the last few decades scientific computing has emerged and recognized as the third pillar of science. Now, in most scientific disciplines, theoretical and experimental studies are linked to computer analysis. In order for the graduate student to be able to stand with claims in the modern scientific and work environment, knowledge in computational techniques is considered a necessary qualification.
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General Competences |
The course aims to enable the student to:
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Syllabus
- Vector and matrix definition and calculations
- Basic commands and functions
- Graphic representation of the numerical results
- Polynomial interpolation: Lagrange Method, Newton's Method
- Numerical integration: Simple and generalized types of numerical integration, rectangular rule, trapezoid rule, Simpson rule, Gauss integration
- Numerical solution of non-linear equations: iterative methods, bisection method, fixed point method, Newton's method
- Numerical solution of linear systems - Direct methods: Gauss elimination, LU decomposition.
Teaching and Learning Methods - Evaluation
Delivery |
In the laboratory | ||||||||||||
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Use of Information and Communications Technology | Use of scientific computing software packages | ||||||||||||
Teaching Methods |
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Student Performance Evaluation |
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Attached Bibliography
See the official Eudoxus site or the local repository of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus:
- Introduction to Numerical Analysis, G.D. Akrivis, V.A. Dougalis, 2010 (in Greek).
- Numerical Linear Algebra, V. Dougalis, D. Noutsos, A. (in Greek).
- A Primer on Scientific Programming with Python, H. P. Langtangen, Springer-Verlag Berlin Heidelberg, 5 Edition, 2016.
- Programming for Computations- MATLAB/Octave, S. Linge, H. P. Langtangen, Springer International Publishing, 2016 (in Greek).