Before diving into Python programming, it's crucial to understand numeric data types, as they are fundamental to many operations.

Python provides two primary numeric data types: **integers** (`int`) and **floating-point numbers** (`float`). These types are built-in, meaning Python can handle them directly without any additional setup. An **integer** is a numeric data type representing whole numbers without any decimal points, such as `1`, `2`, or `456566`. A **float** is a numeric data type representing decimal numbers, like **pi** (`3.14159265359`) or **Euler's number** (`2.71828`).

**Integer** represents whole numbers you commonly encounter in your daily life, such as `1`, `2`, `45`, or `456566`.

On the other hand, **floating numbers** include values like **pi** (`3.14159265359`) and **Euler's number** (`2.71828`).
```python
# Example of an integer
integer_number = 5

# Example of a floating number
float_number_pi = 3.14159265359
```

This course is going to help you dive deeper into data types and try to work with them. Here you will learn basic operations and all ins and outs of numbers, boolean data type, and strings. This course consists of a lot of practical tasks after which you will become a skillful programmer.

Numerical data types are fundamental in Python, forming the backbone of many computational tasks. In this section, you'll dive into the essentials of working with integers and floating-point numbers, performing basic mathematical operations, and understanding the real-world applications of numerical data. You'll also explore critical concepts such as immutability and gain hands-on experience with Python’s built-in functions and tools for handling numbers effectively.

The main goal of this section is to clarify the boolean data types; it's a sub type of numeric data, but indeed it is more challenging. Since it is always better to excel in the more difficult topics, this section is a valuable part of your curriculum.

Strings are a way for us to implement your phrases in Python, that is, to give instructions to users who are the target audience of your program. Indeed, it is always better to be able to work with strings because they should be used in your code. You'll understand why soon.

This chapter consists of practical tasks that combine all the examined topics together with a bit of theory.

Data Types in Python

Numerical Data Type in General