Module 1: Introduction to Python

• What is Python?
  • Overview of Python and its applications
  • Python’s history and community
  • Python’s strengths: readability, simplicity, and portability
• Setting Up the Python Development Environment
  • Installing Python (Windows, macOS, Linux)
  • Introduction to Integrated Development Environments (IDEs): IDLE, PyCharm, Visual Studio Code
  • Writing and running the first Python program (“Hello, World!”)
• Basic Python Syntax
  • Structure of a Python program
  • Comments and documentation in Python (#, docstrings)
  • Indentation and its importance in Python

Module 2: Variables, Data Types, and Operators

• Variables and Constants
  • Defining and using variables
  • Naming conventions for variables
  • Assigning values to variables
• Data Types
  • Primitive data types: integers, floats, strings, booleans
  • Understanding dynamic typing in Python
  • Type conversion (casting between types)
• Operators
  • Arithmetic operators: +, -, *, /, %, //, **
  • Comparison operators: ==, !=, >, <, >=, <=
  • Logical operators: and, or, not
  • Assignment operators: =, +=, -=, *=, /=

Module 3: Control Flow and Decision Making

• Conditional Statements
  • Using if, elif, and else for decision-making
  • Nested conditions
  • Boolean expressions and conditions
• Loops
  • while loop: syntax and example
  • for loop: using range() function
  • Loop control statements: break, continue, pass
• List Comprehension
  • Introduction to list comprehensions for concise looping
  • Examples of basic list comprehensions

Module 4: Functions and Modules

• Defining Functions
  • Function syntax and parameters
  • Return values and the return statement
  • Function arguments (positional, keyword arguments)
• Scope and Lifetime of Variables
  • Global vs. local variables
  • global and nonlocal keywords
• Built-in Functions
  • Commonly used Python functions (print(), input(), len(), type())
• Modules and Libraries
  • Importing and using built-in modules (math, random, datetime)
  • Creating custom Python modules
  • Introduction to import statement and from ... import syntax

Module 5: Data Structures in Python

• Lists
  • Creating, accessing, and modifying lists
  • List methods (append(), remove(), sort(), pop())
  • Iterating over lists
• Tuples
  • Understanding immutable tuples
  • Creating and accessing tuples
  • Tuple unpacking
• Dictionaries
  • Key-value pairs in dictionaries
  • Creating, accessing, and modifying dictionaries
  • Dictionary methods (keys(), values(), items())
• Sets
  • Understanding sets and set operations
  • Creating sets, adding/removing elements
  • Set operations (union, intersection, difference)

Module 6: File Handling

• Working with Files
  • Opening, reading, and writing files in Python
  • File modes: 'r', 'w', 'a', 'r+'
  • Using with statement for automatic file closure
• Reading and Writing Text Files
  • Using read(), readlines() for reading files
  • Using write() and writelines() for writing to files
• Working with CSV Files
  • Introduction to CSV files and csv module
  • Reading and writing CSV files using Python

Module 7: Error Handling and Exceptions

• Introduction to Exceptions
  • What are exceptions and why they occur
  • Common Python exceptions (e.g., ValueError, IndexError, TypeError)
• Handling Exceptions
  • Using try, except to handle errors
  • Catching specific exceptions
  • Using else and finally clauses
• Raising Exceptions
  • Using the raise statement to raise exceptions

Module 8: Object-Oriented Programming (OOP) in Python

• Introduction to OOP
  • What is Object-Oriented Programming?
  • Classes and objects in Python
• Defining Classes and Objects
  • Creating classes and initializing objects using __init__()
  • Instance variables and methods
  • Accessing attributes and calling methods
• Inheritance and Polymorphism
  • Inheriting from other classes
  • Method overriding
  • The super() function
• Encapsulation and Abstraction
  • Public, protected, and private members
  • Using getters and setters
  • Abstract classes and methods (introduction)

Module 9: Working with Libraries and Third-Party Packages

• Installing and Using Third-Party Libraries
  • Introduction to pip (Python package installer)
  • Installing packages from PyPI (e.g., requests, numpy, pandas)
• Popular Python Libraries
  • Working with NumPy for numerical operations
  • Using Pandas for data analysis
  • Introduction to Matplotlib for data visualization