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Basic of Python programming through Hydrology

Category: Projekti

Through this summer school you will learn the first steps of programming in the Python programming language, through interesting examples from Hydrology.

Teacher: DSc Karlo Leskovar

Target group: technical college students, high school seniors, anyone who wants to start programming

Short description:
The goal of this summer school is to introduce students to the basics of Python programming and to provide a framework on how to easily replace spreadsheet programs. It will be shown how to load, analyse and print the actual hydrological data in a diagram. In addition, a basic prediction model based on linear regression, polynomial regression, the K-nearest neighbours method, and Decision-Tree methods will be developed. The developed models will be evaluated to determine their accuracy.


  1. A brief introduction to Hydrology and the Python programming language
    • What is Hydrology?
    • What is Python?
    • Installing the necessary tools - setting up the Python development environment
    • Jupyter Notebook and Anaconda (cell types in the Jupyter Notebook, introduction to the interface)
    • Starting the first program (script)
  2. Basic data types in Python
    • Strings (words, letters)
    • Numbers (integes, floats, doubles)
    • Variables
  3. Data Structures
    • Lists
    • Dictionaries
    • Tuples
  4. Control flow and loops
    • If-else
    • for loop
    • while loop
    • Functions
  5. NumPy i Pandas libraries – working with arrays and table data - loading files (.csv, .xlsx)
  6. Basics of diagram plotting– matplotlib.pyplot
    • Line plots
    • Scatter plots
    • Bar plots
    • Combined plots
  7. Fundamentals of machine learning - regression methods - scikit-learn library
    • Linear regression
    • Polynomial regression
    • K-neighbours
    • Decision Tree
    • Evaluation methods – MSE, MAE, r2

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