Lesson Objectives
By the end of this lesson, you will be able to:
- Install Python correctly on your system
- Configure Visual Studio Code as a professional Python IDE
- Run Python scripts from the terminal
- Understand how this setup scales to data analysis and machine learning
This lesson is foundational.
A poor environment setup will compromise everything that follows.
What Is Python (and Why We Use It)
Python is a high-level, general-purpose programming language designed to prioritize:
- readability
- expressiveness
- rapid development
Python is widely adopted in:
- scientific computing
- statistical analysis
- machine learning
- artificial intelligence
- automation and scripting
In this course, Python is not an end in itself.
It is the computational backbone for advanced analytical workflows.
Installing Python (The Correct Way)
Step 1 — Download Python
Always download Python from the official source:
https://www.python.org
Install Python 3.10 or newer.
Avoid unofficial installers or OS-level package managers unless you know exactly what you are doing.
Step 2 — Installation Options (Critical)
During installation:
Check the option
Add Python to PATH
Do not skip this step
Why this matters:
- The PATH variable allows your system to locate Python
- Without it, Python commands will fail silently or unpredictably
Step 3 — Verify Installation
Open a terminal (Command Prompt / PowerShell / Terminal):
python --version
Expected output:
Python 3.12.x
If this command fails, Python is not properly installed.
Installing Visual Studio Code
Why Visual Studio Code?
Visual Studio Code (VS Code) is a lightweight but professional-grade code editor.
We use VS Code because it:
- scales from beginner to expert
- integrates seamlessly with Python
- supports debugging, linting, and testing
- is widely used in scientific and industrial contexts
Step 1 — Download VS Code
Official website:
Install using default settings.
Step 2 — Install Python Extensions
In VS Code → Extensions panel, install:
- Python (Microsoft)
- Pylance
These extensions provide:
- syntax highlighting
- intelligent autocomplete
- inline error detection
- type inference
This is essential when working with complex analytical code later.
Creating Your First Python Project
Step 1 — Create a Project Folder
Create a folder, for example:
python_course
Open it in VS Code:
File → Open Folder
Step 2 — Create a Python File
Inside the folder, create:
lesson01.py
Writing Your First Python Code
Insert the following code:
print("Hello, Python!")
Code Explanation (Line by Line)
print()is a built-in Python function"Hello, Python!"is a string literal- The function outputs the string to the console
Python is an interpreted language:
the code is executed line by line, without compilation.
Running the Script
Option 1 — Terminal Execution (Recommended)
In the VS Code terminal:
python lesson01.pyExpected output:
Hello, Python!Option 2 — VS Code Run Button
You may also use the Run button.
Both approaches are valid, but terminal execution builds better mental models for later work.
Common Beginner Errors (and Why They Matter)
Missing quotation marks
print(Hello)
Error:
NameError: name 'Hello' is not defined
Explanation:
- Python interprets unquoted text as variable names
Using typographic quotes
print(“Hello”)
Explanation:
- Python only accepts straight quotes (
"or')
Forgetting to save the file
Always save before running.
How This Setup Scales to Advanced Python
This exact environment will later support:
- numerical libraries (
numpy,scipy) - data analysis (
pandas) - visualization (
matplotlib,seaborn) - machine learning (
scikit-learn) - reproducible research pipelines
You will not need to change tools, only add complexity.
FAQ — Frequently Asked Questions
Q: Why not start with Jupyter notebooks?
A: Scripts teach execution flow and structure. Notebooks come later.
Q: Should I install Anaconda?
A: Not yet. Understanding the standard Python ecosystem first is critical.
Q: Is Python suitable for serious scientific work?
A: Yes. Most modern scientific pipelines rely on Python.
Q: Will this work on Windows, macOS, and Linux?
A: Yes. Python is cross-platform.
Exercises
Exercise 1
Print your name.
Exercise 2
Print your age.
Exercise 3
Print two lines of text.
Exercise 4
Print a sentence containing quotes.
Exercise 5
Print a number.
Exercise 6
Print the result of 10 + 5.
Exercise 7
Print a string and a number on the same line.
Exercise 8
Use \\n to print text on two lines.
Exercise 9
Modify the file and run it again.
Exercise 10
Create a new file test.py and run it.
Solutions
Exercise 1
print("Michele")
Exercise 2
print(42)
Exercise 3
print("Line one")
print("Line two")
Exercise 4
print('He said "Python is powerful"')
Exercise 5
print(100)
Exercise 6
print(10 + 5)
Exercise 7
print("Age:", 42)
Exercise 8
print("First line\\nSecond line")
Exercise 9
# Save and re-run the file
Exercise 10
# test.py
print("This is a new file")
Next Lesson Preview
In Lesson 03, we will cover:
- variables
- naming conventions
- Python syntax fundamentals
- how Python stores and manipulates data