Python & DSA β€” Complete Developer Roadmap

🐍 PYTHON LEARNING PATH

Python Roadmap

From Python Fundamentals to Advanced Python, DSA and Interview Preparation

Follow a structured learning path from Python basics to advanced programming, data structures, algorithms and interview preparation.

01 FUNDAMENTALS

Python Fundamentals

Build a strong foundation in Python programming.

What is Python?

Understand Python and why it is widely used.

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Installing Python

Install Python and verify your environment.

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Python Versions

Understand Python 3 and version differences.

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Python Interpreter

Learn how Python executes your programs.

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Python Syntax & PEP 8

Learn Python syntax, comments and basic style conventions.

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Variables & Constants

Store data and understand naming conventions.

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Input & Output

Use print() and input() to interact with users.

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Type Conversion & Dynamic Typing

Convert values and understand Python’s dynamic typing.

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Numbers, Boolean & None

Learn int, float, complex, bool and None.

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Strings

Work with text values and string operations.

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Lists, Tuples, Sets & Dictionaries

Learn Python’s core collection data structures.

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if / elif / else

Control program execution using conditions.

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Loops

Master for, while, range(), break, continue and pass.

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Functions

Define functions, parameters, arguments and return values.

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Function Arguments & Scope

Learn default arguments, kwargs, scope and lambda functions.

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String Indexing & Slicing

Access and manipulate individual parts of strings.

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Formatting & f-Strings

Format strings using f-strings and escape characters.

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Exceptions

Handle runtime errors using Python exceptions.

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File Handling

Open, read, write and append files safely.

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CSV & JSON

Work with common structured data formats.

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02 INTERMEDIATE

Python Intermediate Roadmap

Move beyond the basics and write maintainable Python applications.

Classes & Objects

Understand the foundation of object-oriented Python.

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Methods & Encapsulation

Learn instance, class and static methods.

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Inheritance & Polymorphism

Build reusable object-oriented class hierarchies.

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Modules & Packages

Organize Python programs into reusable modules.

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Functional Programming

Use first-class functions, map(), filter() and reduce().

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Closures, Decorators & Generators

Understand powerful Python function patterns.

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pip & Virtual Environments

Manage dependencies and isolate project environments.

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Testing & Debugging

Debug programs and create automated tests.

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03 ADVANCED + DSA

Advanced Python + Data Structures & Algorithms

Prepare for advanced development, coding interviews and algorithmic problem solving.

Advanced OOP

Master abstract classes, multiple inheritance and dunder methods.

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Context Managers & Iterators

Create reusable advanced Python abstractions.

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Type Hints, Dataclasses & Enums

Write cleaner and more maintainable Python applications.

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Python Internals & Performance

Understand memory, garbage collection and optimization.

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Concurrency & Async Programming

Learn threading, multiprocessing and asyncio.

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Big O & Complexity

Analyze time and space complexity of algorithms.

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Arrays & Strings

Master arrays, strings, two pointers and sliding windows.

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Linked Lists

Learn singly, doubly and circular linked lists.

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Stacks

Understand LIFO structures and stack-based problems.

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Queues

Learn queues, circular queues, deques and priority queues.

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Hashing

Use hash maps and sets for efficient lookup.

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Recursion & Backtracking

Build recursive solutions and explore decision trees.

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Searching

Learn linear search and binary search techniques.

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Sorting Algorithms

Master common comparison and non-comparison sorting algorithms.

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Trees

Learn binary trees, BSTs, traversals, heaps and tries.

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Graph Traversal

Represent graphs and solve BFS and DFS problems.

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Shortest Path Algorithms

Learn Dijkstra and Bellman-Ford algorithms.

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Minimum Spanning Trees

Understand Prim’s and Kruskal’s algorithms.

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Greedy Algorithms

Learn how locally optimal choices can solve problems.

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DP Fundamentals

Understand overlapping subproblems and optimal substructure.

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Classic DP Problems

Practice knapsack, LCS, LIS and grid problems.

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Problem-Solving Techniques

Learn divide-and-conquer, bit manipulation and common patterns.

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Advanced Data Structures

Explore DSU, segment trees and Fenwick trees.

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