Intro to Python Course

This folder contains all the necessary materials for the Intro to Python given by Professor João B. Duarte (https://www.novasbe.unl.pt/en/faculty-research/faculty/faculty-detail/id/126/joao-duarte). These files introduce fundamental programming concepts using Python, along with practical exercises and problem sets. Here's a breakdown of the contents:

  1. 00_Install_Anaconda.ipynb – Step-by-step instructions for setting up the Python environment using Anaconda.
  2. 01_Intro_Programming.ipynb – A beginner-friendly introduction to basic programming concepts in Python.
  3. 02_Introduction_to_Jupyter_Notebooks.ipynb – Guide on using Jupyter Notebooks for interactive coding.
  4. 03_datatypes_strings_numbers_and_variables.ipynb – Covers Python data types, variables, and operations on strings and numbers.
  5. 04_lists_tuples_and_sets.ipynb – Introduction to Python's key data structures: lists, tuples, and sets.
  6. 05_if_statements.ipynb – Explains conditional statements for decision-making in code.
  7. 06_while_loops_and_user_input.ipynb – Teaches while loops and handling user input in Python.
  8. 07_introduction_to_functions.ipynb – Basics of writing and using functions in Python.
  9. 08_some_more_functions.ipynb – Expands on advanced function concepts and usage.
  10. 09_classes_and_OOP.ipynb – Introduction to Object-Oriented Programming (OOP) in Python.
  11. 10_numpy_library.ipynb – Basics of NumPy for numerical computing and array operations.
  12. 11_matplotlib_library.ipynb – Introduction to Matplotlib for data visualization.
  13. Problem set 1.ipynb – Practical exercises to reinforce the concepts learned throughout the course.

While it is not mandatory for students to complete all these exercises, this course is an extremely useful resource throughout the Macroeconometrics course, especially for those who have never had the opportunity to learn how to code in Python. We encourage you to use these materials as a reference and practice tool.