SylabUZ
| Course name | Programming in Statistical Software Packages |
| Course ID | 11.2-WK-CSEEP-PSSP-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 2023/2024 |
| Semester | 6 |
| ECTS credits to win | 3 |
| 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 |
| Project | 30 | 2 | - | - | Credit with grade |
Acquiring skills in designing and writing computational scripts in a chosen software
Basic knowledge in the fields of linear algebra, analysis, algorithms and data structures, probability calculus, and mathematical statistics
As part of the course, the student will become familiar with the computational capabilities of a selected high-level programming language, methods of defining functions, and techniques for creating custom libraries. The ability to create a graphical interface allows for the development of a fully functional program
The classes will be conducted on three levels. In the first one, students will be introduced to basic computational, graphical, and data processing problems, along with methods for their solutions. The second level will focus on presenting data analysis problems for individual or group solutions, and the solutions or partial solutions will be presented in the group forum. A correctness analysis will be conducted. In the third level, each student will be assigned a project topic to work on. Partial solutions will be presented in the group forum.
| Outcome description | Outcome symbols | Methods of verification | The class form |
The final grade for the subject is determined by the assessment of participation in classes and the level of preparedness for classes (30%), as well as the grade for the project (70%).
Modified by dr Ewa Synówka (last modification: 10-04-2024 20:37)
