(in Polish) Wprowadzenie do programowania w języku Python 2400-EM2WPJP

Course Outline:

Python basics: Anaconda Navigator, virtual environments, code editors, Jupyter Notebook
Variable types and basic data structures: lists, tuples, sets, dictionaries; control flow (conditional statements, loops, exceptions)
Functions: arguments, local and global variables, lambda functions, recursion
NumPy: vectors, matrices, random numbers, mathematical functions
Pandas: working with DataFrames (filtering, grouping, merging data)
Pandas in practice: working with larger datasets (cleaning, descriptive statistics, text data, dates, creating custom functions)
Importing data: csv, Excel, pickle files
Working with statistical datasets: Eurostat, World Bank, OECD
Data visualization: Matplotlib and Seaborn, creating visually appealing charts
Project consultations
Project presentations (2 sessions)

Assessment:

The course is assessed through a team project. The project focuses on the use of Python for data analysis — for example, an empirical study of a selected social phenomenon. The project includes both a Python script and a final presentation.
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KNOWLEDGE

The student can explain the difference between an integrated development environment (IDE) and a text editor.
The student is aware of the existence of various data structures, including non-basic ones, and knows which structure is appropriate for solving specific problems.
The student understands the applications of core Python libraries and knows how to search for additional libraries suited to specific tasks.
The student can distinguish between common data formats and knows which tools should be used to load them.
The student knows how to prepare an empirical analysis based on statistical datasets.
The student knows where to look for programming-related information.

SKILLS

The student can configure a virtual environment and select an appropriate code editor according to their needs.
The student is capable of analyzing data independently retrieved from online sources for use in a bachelor's or master's thesis.
The student can write code that efficiently solves a given problem.
The student can search for problem solutions using search engines and adapt the results to their context.
The student can use generative artificial intelligence tools to support coding and customize the proposed solutions.
The student can create visually engaging charts and data visualizations.

COMPETENCES

The student understands that both individual work and continuous learning in collaboration with others are essential to succeed in programming.
The student is aware that the problem they face has likely been solved before and that it is valuable to learn from others' experience.
The student can present their work and communicate conclusions based on data analysis.