Python Programming Course Content covering Basic to Advanced levels. This structure is ideal for learners aiming to build a solid foundation and grow into advanced Python roles like automation engineer, data analyst, backend developer, or ML engineer

• Module 1: Python Basics

  1 min read

  • What is Python?
  • Installing Python & IDEs (PyCharm, VS Code, Jupyter)
  • Python vs Other Languages
  • Writing your first Python program
    

• Module 2: Control Flow and Loops

  1 min read

  • Conditional Statements (if, elif, else)
  • Loops: for, while
  • Loop Control: break, continue, pass
  • range(), enumerate(), zip()
    

• Module 3: Data Structures in Python

  1 min read

  • Lists, Tuples, Sets, and Dictionaries
  • List/Dict Comprehensions
  • Built-in Functions (len, min, max, etc.)
  • Sorting and Nested Structures
    
    

• Module 4: Functions and Modules

  1 min read

  • Defining and Calling Functions
  • *args, **kwargs
  • Lambda Functions
  • Recursion
  • Modules and Packages
  • import, from ... import, __name__ == '__main__'
    

• Module 5: File Handling

  1 min read

  • Reading and Writing Text/Binary Files
  • Working with with context manager
  • File Methods: read(), write(), seek(), tell()
  • CSV & JSON File Handling
    
    

• Module 6: Object-Oriented Programming (OOP)

  1 min read

  • Classes and Objects
  • Constructors and Destructors
  • Inheritance, Polymorphism, Encapsulation
  • @classmethod, @staticmethod, __str__, __repr__
    
  • Operator Overloading
    
    

• Module 7: Exception Handling

  1 min read

  • Try, Except, Finally
  • Custom Exceptions
  • Raising Exceptions
  • Using assert statements
    
    

• Module 8: Python Standard Libraries & Utilities

  1 min read

  • os, sys, math, random, datetime, re
  • Command-line Arguments
  • Working with Environment Variables
    
    

• Module 9: Working with External Libraries (Intro to Advanced)

  1 min read

  • Installing Packages with pip
  • Using virtualenv
    Overview of Popular Libraries:
  • NumPy, Pandas – Data Analysis
  • Matplotlib, Seaborn – Visualization
  • Requests – Web APIs
  • BeautifulSoup / Scrapy – Web Scraping
    
    
    

• Module 10: Advanced Python Topics

  1 min read

  • Iterators and Generators
  • Decorators
  • Context Managers (__enter__, __exit__)
  • Closures
  • Multithreading and Multiprocessing
  • Memory Management and Garbage Collection
    
    

• Module 11: Python for Applications (Optional Specializations)

  1 min read

  A. Web Development with Flask/Django

  • REST API with Flask
  • Template Rendering, Routing, Sessions
    
    

  B. Data Science & Machine Learning

  • Data Cleaning with Pandas
    
  • Plotting with Matplotlib
  • Intro to scikit-learn, Linear Regression
    
    C. Automation & Scripting
  • Automate Excel, PDF, Email

  Web Automation with Selenium
  
  D. Database Programming

  • sqlite3, MySQL connectivity
  • ORM with SQLAlchemy