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Python Classes

🐍Python Programming Roadmap

Level 1: Core Python (Beginner)

This foundational level is for absolute beginners. Covers the core fundamentals. No prior coding knowledge needed.

Estimated Time to Complete: 25-30 Hours

1. Introduction to Python (2 Hours)

  • History, features, and modern applications of Python.
  • Installing Python and setting up an IDE (e.g., Anaconda, Colab, Jupyter Notebook etc).
  • Running your first scripts (using the interactive shell and .py files).
  • Understanding PEP 8 style guidelines for writing clean code.

2. Basic Syntax & Data Types (5 Hours)

  • Variables, keywords, and identifiers.
  • Using comments and understanding Python’s indentation rules.
  • Numeric types: int, float, complex.
  • Strings: Creation, indexing, slicing, and common methods.
  • The Boolean type (True/False) and truth values.
  • Type Casting: Converting between data types (e.g., int() to str()).

3. Operators (2 Hours)

  • Arithmetic (+, -, *, /), assignment (=, +=), and comparison (==, >) operators.
  • Logical (and, or), identity (is), and membership (in) operators.

4. Core Data Structures (6 Hours)

  • Lists: Creating, indexing, slicing, and using list methods.
  • Tuples: Understanding immutability and tuple methods.
  • Sets: Working with unique items and performing set operations (union, intersection).
  • Dictionaries: Storing and accessing data using key-value pairs.

5. Control Flow (5 Hours)

  • Conditional logic with if, elif, and else statements.
  • Looping with for (over sequences) and while (based on a condition).
  • Controlling loops with break, continue, and pass.

6. Functions (6 Hours)

  • Defining and calling your own reusable functions.
  • Using parameters: positional, keyword, and default arguments.
  • Handling a variable number of arguments with *args and **kwargs.
  • Understanding return values and creating simple lambda functions.
  • Variable Scope: Local vs. Global variables.

7. File I/O (2 Hours)

  • Reading from and writing to text (.txt) and CSV (.csv) files.
  • Using the with statement for safe and automatic file handling.

Level 2: Intermediate Python

This level focuses on writing efficiently, modular, and professional-grade code. You’ll move beyond simple scripts to build robust and scalable programs using Object-Oriented principles.

Estimated Time to Complete: 25-30 Hours

1. Object-Oriented Programming (OOP) (15 Hours)

  • Understanding Classes, Objects, attributes, and methods.
  • The __init__ constructor for initializing objects.
  • Mastering the four pillars of OOP:
    • Inheritance
    • Encapsulation
    • Polymorphism
    • Abstraction
  • Using class methods and static methods.

2. Modules & Packages (5 Hours)

  • Importing modules from the Python Standard Library.
  • Creating your own custom modules and packages.
  • Installing and managing third-party packages with pip.

3. Exception Handling (4 Hours)

  • Gracefully handling errors with try, except, else, and finally.
  • Catching multiple specific exceptions.
  • Raising your own custom exceptions.

4. Advanced Data Structures & Comprehensions (5 Hours)

  • Writing concise List, Dictionary, and Set Comprehensions.
  • Using the collections module: Counter, defaultdict, deque.

5. Virtual Environments (2 Hours)

  • Understanding why code isolation is crucial.
  • Creating and managing virtual environments with venv.

Level 3: Advanced Python & Specialization

This level covers high-performance programming concepts and provides a launchpad into specialized fields like web development and data science.

Estimated Time to Complete: 25-30 Hours

1. Advanced Programming Concepts (10 Hours) 

  • Iterators & Generators: Understanding the iterator protocol (__iter__, __next__) and creating memory-efficient data streams with the yield keyword.
  • Generator Expressions: A high-performance, memory-efficient alternative to list comprehensions.

2. Specialization: Web Development (30 Hours) 

  • Django: A high-level framework for rapid development. Learn Models, Views, Templates, and its powerful ORM.
  • Flask: A lightweight micro-framework for smaller applications and APIs. Learn routing, templates, and request handling.
  • REST APIs: Build APIs with Django REST Framework or Flask-RESTful.

3. Specialization: Data Science & Machine Learning (40 Hours) 

  • NumPy: The fundamental package for scientific computing, focusing on ndarrays and vectorized operations.
  • Pandas: The ultimate tool for data manipulation and analysis using DataFrames and Series.
  • Matplotlib & Seaborn: Creating a wide range of static, animated, and interactive visualizations.
  • Scikit-learn: Applying machine learning models for regression, classification, and clustering.
  • TensorFlow / PyTorch: An introduction to building and training deep learning models.