Introduction to Data Types and Control Structures

Basic Data Types:
- Integer: Whole numbers, e.g. x = 5
- Float: Decimal numbers, e.g. y = 5.0
- String: Sequence of characters, e.g. name = "Alice"
- Boolean: Represents True or False
Compound Data Types:
- List: Ordered, mutable collection, e.g. my_list = [1, 2, 3]
- Tuple: Ordered, immutable collection, e.g. my_tuple = (1, 2, 3)
- Set: Unordered collection of unique elements, e.g. my_set = {1, 2, 3}
- Dictionary: Key-value pairs, e.g. my_dict = {'key': 'value'}

Conditional Statements:
- if, elif, else statements for branching logic.
Loops:
- For Loop: Iterates over a sequence, e.g. for i in range(5):
- While Loop: Continues while a condition is true, e.g. while x < 5:
Control Flow Tools:
- break: Exits the current loop.
- continue: Skips the current iteration.
- pass: Does nothing; a placeholder.

Defining Functions:
- Use def keyword, e.g. def my_function(param):
Function Parameters:
- Positional: Based on order.
- Keyword: Specified by name, e.g. my_function(param=value)
- Default: Provides default values, e.g. def func(a, b=2):
Return Statement:
- Use return to send back a value from function.

Classes and Objects:
- Class: Blueprint for creating objects, e.g. class MyClass:
- Object: Instance of a class.
Attributes and Methods:
- Attributes: Variables that belong to a class.
- Methods: Functions defined inside a class.
Inheritance:
- Mechanism to create a new class based on an existing class, e.g. class ChildClass(ParentClass):
Encapsulation:
- Restrict access to certain components, using private attributes or methods.
Polymorphism:
- Ability to use a common interface for different underlying forms (data types).

Standard Library:
- Includes built-in modules like math, datetime, and os.
Popular Libraries:
- NumPy: For numerical computing.
- Pandas: For data manipulation and analysis.
- Matplotlib: For plotting and data visualization.
- Requests: For handling HTTP requests.
Web Frameworks:
- Flask: Lightweight framework for web applications.
- Django: Full-featured web framework that follows the MVC pattern.
Machine Learning Libraries:
- Scikit-learn: For machine learning algorithms.
- TensorFlow: For deep learning applications.
- PyTorch: Another popular library for machine learning and deep learning.

Basic data types include Integer (whole numbers), Float (decimal numbers), String (character sequences), and Boolean (True/False values).
Compound data types consist of List (ordered and mutable collections), Tuple (ordered and immutable collections), Set (unordered unique elements), and Dictionary (key-value pairs).

Conditional statements (if, elif, else) allow for branching logic in code execution.
Loops facilitate repetition:
- For Loop iterates over sequences (e.g., for i in range(5):).
- While Loop continues executing as long as a condition remains true (e.g., while x < 5:).
Control flow tools include break (exits loops), continue (skips current iteration), and pass (placeholder that does nothing).

Functions are defined using the def keyword followed by the function name and parameters (e.g., def my_function(param):).
Function parameters can be positional, keyword (specified by name), or default (providing predefined values).
The return statement is used to send back a value from a function.

A Class serves as a blueprint for creating Objects, while an Object is an instance of a class.
Attributes are variables within a class, while Methods are functions that are defined inside a class.
Inheritance allows the creation of a new class based on an existing one (e.g., class ChildClass(ParentClass):).
Encapsulation restricts access to certain elements within a class by using private attributes or methods.
Polymorphism enables the use of a common interface for different data types, enhancing flexibility.

The Standard Library offers built-in modules, which include math, datetime, and os, enhancing functionality.
Popular libraries include:
- NumPy for numerical computations.
- Pandas for data manipulation and analysis.
- Matplotlib for data visualization and plotting.
- Requests for managing HTTP requests.
Web frameworks:
- Flask is a lightweight option for web applications.
- Django is a comprehensive framework that adheres to the MVC pattern.
Machine Learning Libraries:
- Scikit-learn provides tools for machine learning algorithms.
- TensorFlow is used for deep learning applications.
- PyTorch is another widely-used library for machine learning and deep learning tasks.