SylabUZ
Course name | Mathematical Software |
Course ID | 11.9-WK-CSEEP-MS-S22 |
Faculty | Faculty of Exact and Natural Sciences |
Field of study | computer science and econometrics |
Education profile | academic |
Level of studies | First-cycle studies leading to Bachelor's degree |
Beginning semester | winter term 2022/2023 |
Semester | 6 |
ECTS credits to win | 2 |
Course type | optional |
Teaching language | english |
Author of syllabus |
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The class form | Hours per semester (full-time) | Hours per week (full-time) | Hours per semester (part-time) | Hours per week (part-time) | Form of assignment |
Laboratory | 30 | 2 | - | - | Credit with grade |
The familiarization of the students with the capabilities of the mathematical software supporting the work of mathematicians and engineers (like SciPy).
Computer Programming 1.
To illustrate the capabilities of the mathematical software, during laboratory classes students will write computer programs solving some mathematical problems. In addition, in order for students to become more skilled at using given mathematical software, lists of assignments will be provided.
Outcome description | Outcome symbols | Methods of verification | The class form |
Learning outcomes will be verified through two tests consisted of exercises of different degree of difficulty. A grade, determined by the sum of points from these two tests, is a basis of assessment.
1. Mark Lutz, David Ascher, Learning Python, 5th Edition, O'Reilly Media, Inc., 2013.
1. Robert Johansson, Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib, 2nd edition, Apress, 2018.
Modified by dr Tomasz Małolepszy (last modification: 29-12-2023 21:12)