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Lecturer(s)
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Dobešová Zdena, doc. Ing. Ph.D.
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Vojtěchovská Michaela, Mgr.
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Course content
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1. Python programming environment (installation, setup, AI code generation) 2. Basic data handling (CSV, JSON, Python functions, installing packages and converting to other formats) 3. Jupyter Notebook for interactive coding (principles, use in ArcGIS Pro) 4. Numerical calculations in NumPy (average, sum and other aggregation functions, multi-dimensional arrays, ...) 5. Data analysis in Pandas (DataFrame, sorting, sorting and joining tables) 6. Data visualization in Matplotlib (graphing and customizing axes, titles and legends, interactive visualization) 7. GeoPandas for spatial data (GeoDataFrame, spatial data visualization, basic spatial operations) 8. Fundamentals of machine learning in Sci-kit (model selection and evaluation) 9. Convolutional neural networks from TensorFlow library (image classification using CNN, TensorFlow setup, test and training set) 10. Defense of semester project
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Learning activities and teaching methods
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Lecture, Laboratory Work
- Homework for Teaching
- 2 hours per semester
- Semestral Work
- 15 hours per semester
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Learning outcomes
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This course provides a basic overview and skills in data processing using the Python programming language. The acquired practical knowledge and procedures will be the basis for programming the semester project elaborated by students.
This course is aimed at acquiring knowledge and skills of programming in Python.
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Prerequisites
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Application of knowledge from previous courses.
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Assessment methods and criteria
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Mark, Seminar Work, Written exam
Verification of results: oral and written. Other requirements: semester project, presentation, 80% attendance.
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Recommended literature
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Data Camp courses: Writing function, Geometries and shapefiles.
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Diener M. Python Geospatial Analysis Cookbok. 2015.
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Chollet, F. (2019). Deep learning v jazyku Python: knihovny Keras, Tensorflow. Praha, Grada Publishing. Knihovna programátora (Grada).
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Pecinovský, R. (2022). Python - knihovny pro práci s daty pro verzi 3.11. Grada.
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