Module 1: Basic Python Programming

1.1 Introduction to Python

• Overview of Python and its applications
• Setting up the Python development environment (Installation of Python and IDEs like PyCharm, VSCode, Jupyter Notebooks)
• Writing and running the first Python program (Hello, World!)
• Python syntax and structure

1.2 Python Basics

• Variables and data types (int, float, string, boolean)
• Constants and variable naming conventions
• Type conversion (casting between types)
• Arithmetic, comparison, and logical operators

1.3 Control Flow

• Conditional Statements: if, elif, else
• Logical operators (and, or, not)
• Loops: for loop, while loop
  • Using range() and looping techniques
  • Control flow in loops (break, continue, pass)

1.4 Functions

• Defining functions using def keyword
• Parameters and return values
• Variable scope (local and global variables)
• Recursion in Python

1.5 Data Structures

• Lists and list operations (indexing, slicing, appending, sorting)
• Tuples and tuple operations
• Sets and set operations (union, intersection, difference)
• Dictionaries (key-value pairs, adding, removing, accessing values)

1.6 File Handling

• Opening, reading, and writing files
• Working with text files using open()
• Using with to handle file operations (auto-close)
• Reading and writing CSV files

Module 2: Intermediate Python Programming

2.1 Object-Oriented Programming (OOP) Basics

• Introduction to OOP: Concepts and Terminology
  • Classes and objects
  • Instance variables and methods
  • The __init__() constructor
• Inheritance and Polymorphism
  • Method overriding
  • Using super()
• Encapsulation: Public, Protected, Private Members
  • Getter and setter methods

2.2 Working with Modules and Packages

• Importing and using Python modules
• Creating and using custom Python packages and modules
• Introduction to built-in Python libraries (e.g., math, random, datetime)

2.3 Exception Handling

• Introduction to errors and exceptions
• Try, except, and finally blocks
• Raising exceptions with raise
• Handling specific exceptions (e.g., ValueError, IndexError)
• Custom exceptions and error handling in Python

2.4 Advanced Data Structures

• Advanced list techniques (list comprehension)
• Dictionaries and sets in-depth
  • Nested dictionaries and sets
• Collections module: namedtuple(), Counter, deque, defaultdict

2.5 Working with Regular Expressions

• Introduction to regular expressions (regex) in Python
• Using re module
  • Matching patterns, searching, and replacing
• Practical examples of regex (validating email, phone number)

2.6 Working with JSON and XML

• Parsing and writing JSON data
• Introduction to json module
• Parsing XML with ElementTree

Module 3: Advanced Python Programming

3.1 Advanced Object-Oriented Programming (OOP)

• Abstract Classes and Interfaces
  • Using the abc module and ABC class
  • Abstract methods
• Multiple Inheritance in Python
• Class and Static Methods
  • @classmethod, @staticmethod
• Magic Methods (Dunder methods)
  • __str__(), __repr__(), __len__(), __add__()

3.2 Working with Databases (SQL)

• Introduction to databases in Python
• Connecting Python to databases using SQLite3 and MySQL
• Executing SQL queries (INSERT, SELECT, UPDATE, DELETE)
• Using sqlite3 module for database management
• Fetching data from databases and processing it in Python

3.3 Advanced Functional Programming in Python

• Understanding Functional Programming concepts
• Using lambda functions and filter(), map(), reduce()
• List comprehensions and generator expressions
• Higher-order functions and decorators
• Working with functools module

3.4 Python Multithreading and Concurrency

• Introduction to threads and processes
• Using threading module for parallelism
• Thread synchronization and locks
• Understanding the Global Interpreter Lock (GIL)
• Using multiprocessing module for concurrent execution
• Asynchronous programming with asyncio

3.5 Performance Optimization

• Profiling Python code using cProfile
• Understanding time complexity (Big-O notation)
• Optimizing loops and function calls
• Using built-in Python modules for performance (itertools, functools, collections)
• Memory management and garbage collection in Python

3.6 Python for Web Development (Optional)

• Introduction to web frameworks: Flask or Django
• Creating a simple web application with Flask
• Working with templates and rendering HTML
• Handling HTTP requests and routing
• Storing data in a database with Flask/Django

3.7 Networking in Python

• Introduction to networking with Python
• Using socket module for networking
• Creating client-server applications with Python
• Working with protocols (TCP/IP, UDP)
• Sending and receiving data through sockets

Module 4: Final Project and Practice

4.1 Capstone Project

• Designing and developing a Python project based on course concepts
• Applying Object-Oriented Programming, Data Structures, and advanced features
• Final project examples:
  • Python-based text-based game
  • Web scraping application
  • Command-line application for data processing
  • Database-driven application with GUI

4.2 Code Review and Optimization

• Reviewing and improving project code
• Debugging, profiling, and testing
• Best practices for writing efficient and maintainable Python code

4.3 Final Assessment

• Hands-on practical exam
• Coding challenges to test problem-solving and understanding of concepts