Basic information
- Field of study
- Geospatial Computer Science
- Major
- Remote Sensing and GIS
- Organisational unit
- Faculty of Geo-Data Science, Geodesy, and Environmental Engineering
- Study level
- Second-cycle (engineer) programme
- Form of study
- Full-time studies
- Profile
- General academic
- Didactic cycle
- 2024/2025
- Course code
- DGEITGS.IIi2.07205.24
- Lecture languages
- English
- Mandatoriness
- Obligatory
- Block
- Major Modules
- Course related to scientific research
- Yes
|
Period
Semester 2
|
Method of verification of the learning outcomes
Exam
Activities and hours
Lectures:
15
Project classes: 30 |
Number of ECTS credits
4
|
Goals
| G1 | The module allows recognizing possibilities of using Python as a tool for solving geoinformation problems. |
Course's learning outcomes
| Code | Outcomes in terms of | Learning outcomes prescribed to a field of study | Methods of verification |
| Knowledge – Student knows and understands: | |||
| W1 | rules of Python programming language | GEI2A_W02 | Examination |
| Skills – Student can: | |||
| U1 | extend geoinformation tools functionality using Python language | GEI2A_U02 | Examination |
| U2 | create programs using Python language | GEI2A_U02 | Examination |
| Social competences – Student is ready to: | |||
| K1 | creativity in programming | GEI2A_K03 | Activity during classes |
| K2 | language usage for application extension | GEI2A_K03 | Activity during classes |
Program content ensuring the achievement of the learning outcomes prescribed to the module
Student workload
| Activity form | Average amount of hours* needed to complete each activity form | |
| Lectures | 15 | |
| Project classes | 30 | |
| Preparation for classes | 15 | |
| Realization of independently performed tasks | 30 | |
| Examination or final test/colloquium | 2 | |
| Contact hours | 1 | |
| Preparation of project, presentation, essay, report | 10 | |
| Student workload |
Hours
103
|
|
| Workload involving teacher |
Hours
45
|
|
* hour means 45 minutes
Program content
| No. | Program content | Course's learning outcomes | Activities |
| 1. |
Advanced scripts and program flow control. Script authoring tools refresh. Error correction and interpretation. Conditionals, loops and exception handling. Some classes may be conducted as webinar. |
U1, U2, K1, K2 | Project classes |
| 2. |
Python basics rehash. Data types, their representation and complex structures. Advanced Scripts and program flow control. Conditional structures, loops and function definitions. Difference between interpreter and compiler. Exception handling. Input/output procedures. Some classes may be conducted as webinar. |
W1, K1 | Lectures |
Extended information/Additional elements
Teaching methods and techniques :
Remote learning trough UPEL and webinar tools., E-learning, Group work, Lectures
| Activities | Methods of verification | Credit conditions |
|---|---|---|
| Lectures | Activity during classes, Examination | Positive grade |
| Project classes | Activity during classes, Examination | Positive grade |
Conditions and the manner of completing each form of classes, including the rules of making retakes, as well as the conditions for admission to the exam
Classes are graded based on performing excercises and activity. Taking exam is conditioned by positive class grade. In case of a failed exam attempt, there will be possible 2 more tries. Retrying failed attempt does not have the impact on final grade. Preliminary requirement for the exam is to pass project classes.
Method of determining the final grade
To pass project classes assignment have to be fulfilled. Lectures and project classes final grade will be based on the class grade and final exam at the end of the semester.
Manner and mode of making up for the backlog caused by a student justified absence from classes
Student that is absent ought to learn material themselves.
Prerequisites and additional requirements
Ability to understand English.
Computer usage knowledge.
Basic Python language familiarity (f.e. DGI-2-107-TG-s course).
Ability to use a web browser.
Rules of participation in given classes, indicating whether student presence at the lecture is obligatory
Students participate in classes, covering the subject's content according to the syllabus. Students should continuously ask questions and clarify any doubts. Recording of the lecture requires the instructor's consent. Project classes: Students carry out practical work aimed at achieving the competencies outlined in the syllabus. The evaluation includes the execution of the project and the final outcome.
Literature
Obligatory- 1. Lutz Mark: “Learning Python, 5th edition”. 2013,
- 2. Dawson Michael: “Python Programming for the Absolute Beginner, 3rd Edition”, 2010
- 3. Documentation and online courses: http://pl.python.org
- 4. Summerfield Mark: “Rapid GUI Programming with Python and Qt”. Prentice Hall 2008
- 5. PyQt documentation: http://pyqt.sourceforge.net/Docs/PyQt5/
Scientific research and publications
Publications- Twardowski M., Pastucha E., Kolecki J., 2016: Performance of the automatic bundle adjustment in the virtualized environment
- Hejamnowska B., Twardowski M., Żądło A., 2021: An application of the “traffic lights” idea to crop control in integrated administration control system
- Rzonca A., Twardowski M., 2022, The lidargrammetric model deformation method for altimetric UAV-ALS data enhancement