PythonSyllabus

• Module 1: Introduction to Python

  • Overview of Python
  • Installing Python
  • Setting Up the Development Environment
  • Writing and Running Your First Python Program
  • Python IDEs (IDLE, PyCharm, VSCode)

• Module 2: Python Basics

  • Python Syntax and Semantics
  • Variables and Data Types
  • Basic Operators (Arithmetic, Comparison, Logical)
  • Input and Output
  • Comments and Documentation

• Module 3: Control Flow

  • Conditional Statements (if, elif, else)
  • Looping Constructs (for, while)
  • Loop Control Statements (break, continue, pass)

• Module 4: Functions and Modules

  • Defining and Calling Functions
  • Function Arguments and Return Values
  • Lambda Functions
  • Modules and Packages
  • The import Statement
  • Built-in Functions

• Module 5: Data Structures

  • Lists and List Operations
  • Tuples and Tuple Operations
  • Dictionaries and Dictionary Operations
  • Sets and Set Operations
  • List Comprehensions
  • Dictionary and Set Comprehensions

• Module 6: Strings

  • String Literals and Operations
  • String Methods
  • String Formatting
  • Regular Expressions

• Module 7: File Handling

  • Reading from and Writing to Files
  • Working with File Paths
  • Handling Exceptions in File Operations
  • Best Practices for Configuration Management

• Module 8: Exception Handling

  • Introduction to Exceptions
  • The try, except, else, finally Blocks
  • Custom Exceptions
  • Best Practices for Error Handling

• Module 9: Object-Oriented Programming (OOP)

  • Introduction to OOP
  • Classes and Objects
  • Inheritance
  • Encapsulation
  • Polymerphoism
  • Magic Methods and Operator Overloading

• Module 10: Standard Libraries and Modules

  • The math Module
  • The datetime Module
  • The collections Module
  • The itertools Module
  • The os and sys Modules

• Module 11: Working with External Libraries

  • Installing and Using External Libraries (pip)
  • Popular Libraries (requests, NumPy, Pandas, Matplotlib)

• Module 12: Python for Data Science

  • Introduction to NumPy
  • Data Manipulation with Pandas
  • Data Visualization with Matplotlib and Seaborn
  • Basic Statistical Analysis

• Module 13: Web Development with Python

  • Introduction to Web Frameworks (Flask, Django)
  • Setting Up a Flask Application
  • Routing and Templates in Flask
  • Setting Up a Django Project
  • Models, Views, and Templates in Django

• Module 14: Testing and Debugging

  • Writing Unit Tests with unittest
  • Test-Driven Development (TDD)
  • Debugging Techniques
  • Using Debugging Tools (pdb)

• Module 15: Advanced Topics

  • Generators and Iterators
  • Decorators
  • Context Managers
  • Metaclasses

• Module 16: Best Practices and Project Development

  • Writing Clean and Readable Code
  • Code Documentation
  • Version Control with Git
  • Developing a Python Project from Scratch
  • Packaging and Distributing Python Code