Guided path

Python roadmap

Follow modules in order. Start with Python Introduction, then continue through data types, functions, OOP, and databases.

1. 1

   Python Introduction

   Understand what Python is, where it is used, and why it is popular.

2. 2

   Basic Program Structure and Input/Output

   Learn how Python programs are written, how output is displayed, and how input is read dynamically.

3. 3

   Data Types

   Understand Python's built-in data types and when to use each one.

4. 4

   Type Casting and Fundamental Conversions

   Learn how to convert one data type into another safely and correctly.

5. 5

   Operators and Expressions

   Learn how Python expressions are formed using different operators.

6. 6

   String Handling

   Learn string operations, methods, examples, and problem-solving patterns.

7. 7

   Mutable and Immutable Objects

   Understand object mutability and copying behavior in Python.

8. 8

   Collections Deep Dive

   Learn Python collection types deeply: list, tuple, set, frozenset, dictionary, and mixed combinations.

9. 9

   Flow Control Statements

   Learn decision-making, loops, transfer statements, and nested control flow.

10. 10

    Functions

    Learn function creation, parameters, arguments, scope, lambda, and special functions filter/map/reduce.

11. 11

    Comprehension Techniques

    Learn concise data transformation using list, set, dictionary, and tuple comprehensions.

12. 12

    Lambda and Special Functions

    Learn anonymous functions and important functional-programming helpers.

13. 13

    Iterators, Generators, and Decorators

    Learn advanced Python execution patterns and reusable behavior wrapping.

14. 14

    Modules and Packages

    Learn how to organize Python code into modules and packages.

15. 15

    Exception Handling

    Learn how to handle runtime errors and create custom exceptions.

16. 16

    Files, Pickling, CSV, JSON, and OS Operations

    Learn file handling and common data exchange formats.

17. 17

    Object-Oriented Programming

    Learn Python OOP concepts such as classes, objects, inheritance, abstraction, encapsulation, and polymorphism.

18. 18

    Regular Expressions

    Learn pattern matching and text processing using Python's re module.

19. 19

    Multithreading

    Learn thread-based application development and synchronization basics.

20. 20

    Networking Programming

    Learn the basics of developing network-based applications in Python.

21. 21

    Python Database Communication

    Learn how Python communicates with databases and how database queries are organized.

22. 22

    Extra Practice and Revision

    Revise concepts through examples, question banks, interview questions, and small utility projects.

23. 23

    NumPy

    Create, index, filter, reshape, and analyze numeric arrays with NumPy, the base library for data science and machine learning.

24. 24

    pandas

    Load, clean, filter, group, and combine table-shaped data with pandas Series and DataFrames.

25. 25

    Matplotlib

    Draw clear line, bar, scatter, histogram, and pie charts with Matplotlib, arrange them in subplots, and save them as files.

26. 26

    Seaborn

    Explore tidy data with Seaborn's relational, distribution, categorical, matrix, and regression charts, then theme and finish them.

27. 27

    Scikit-learn

    Train, evaluate, and tune regression, classification, and clustering models with scikit-learn, from train and test splits to pipelines and saved models.