Complete roadmap to learn Python and Data Structures & Algorithms (DSA) in 2 months

### Week 1: Introduction to Python

Day 1-2: Basics of Python
- Python setup (installation and IDE setup)
- Basic syntax, variables, and data types
- Operators and expressions

Day 3-4: Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)

Day 5-6: Functions and Modules
- Function definitions, parameters, and return values
- Built-in functions and importing modules

Day 7: Practice Day
- Solve basic problems on platforms like HackerRank or LeetCode

### Week 2: Advanced Python Concepts

Day 8-9: Data Structures in Python
- Lists, tuples, sets, and dictionaries
- List comprehensions and generator expressions

Day 10-11: Strings and File I/O
- String manipulation and methods
- Reading from and writing to files

Day 12-13: Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance, polymorphism, encapsulation

Day 14: Practice Day
- Solve intermediate problems on coding platforms

### Week 3: Introduction to Data Structures

Day 15-16: Arrays and Linked Lists
- Understanding arrays and their operations
- Singly and doubly linked lists

Day 17-18: Stacks and Queues
- Implementation and applications of stacks
- Implementation and applications of queues

Day 19-20: Recursion
- Basics of recursion and solving problems using recursion
- Recursive vs iterative solutions

Day 21: Practice Day
- Solve problems related to arrays, linked lists, stacks, and queues

### Week 4: Fundamental Algorithms

Day 22-23: Sorting Algorithms
- Bubble sort, selection sort, insertion sort
- Merge sort and quicksort

Day 24-25: Searching Algorithms
- Linear search and binary search
- Applications and complexity analysis

Day 26-27: Hashing
- Hash tables and hash functions
- Collision resolution techniques

Day 28: Practice Day
- Solve problems on sorting, searching, and hashing

### Week 5: Advanced Data Structures

Day 29-30: Trees
- Binary trees, binary search trees (BST)
- Tree traversals (in-order, pre-order, post-order)

Day 31-32: Heaps and Priority Queues
- Understanding heaps (min-heap, max-heap)
- Implementing priority queues using heaps

Day 33-34: Graphs
- Representation of graphs (adjacency matrix, adjacency list)
- Depth-first search (DFS) and breadth-first search (BFS)

Day 35: Practice Day
- Solve problems on trees, heaps, and graphs

### Week 6: Advanced Algorithms

Day 36-37: Dynamic Programming
- Introduction to dynamic programming
- Solving common DP problems (e.g., Fibonacci, knapsack)

Day 38-39: Greedy Algorithms
- Understanding greedy strategy
- Solving problems using greedy algorithms

Day 40-41: Graph Algorithms
- Dijkstra’s algorithm for shortest path
- Kruskal’s and Prim’s algorithms for minimum spanning tree

Day 42: Practice Day
- Solve problems on dynamic programming, greedy algorithms, and advanced graph algorithms

### Week 7: Problem Solving and Optimization

Day 43-44: Problem-Solving Techniques
- Backtracking, bit manipulation, and combinatorial problems

Day 45-46: Practice Competitive Programming
- Participate in contests on platforms like Codeforces or CodeChef

Day 47-48: Mock Interviews and Coding Challenges
- Simulate technical interviews
- Focus on time management and optimization

Day 49: Review and Revise
- Go through notes and previously solved problems
- Identify weak areas and work on them

### Week 8: Final Stretch and Project

Day 50-52: Build a Project
- Use your knowledge to build a substantial project in Python involving DSA concepts

Day 53-54: Code Review and Testing
- Refactor your project code
- Write tests for your project

Day 55-56: Final Practice
- Solve problems from previous contests or new challenging problems

Day 57-58: Documentation and Presentation
- Document your project and prepare a presentation or a detailed report

Day 59-60: Reflection and Future Plan
- Reflect on what you've learned
- Plan your next steps (advanced topics, more projects, etc.)

Best DSA RESOURCES: https://topmate.io/coding/886874

Credits: https://t.iss.one/free4unow_backup

ENJOY LEARNING 👍👍

Python CheatSheet 📚 ✅

1. Basic Syntax
- Print Statement: print("Hello, World!")
- Comments: # This is a comment

2. Data Types
- Integer: x = 10
- Float: y = 10.5
- String: name = "Alice"
- List: fruits = ["apple", "banana", "cherry"]
- Tuple: coordinates = (10, 20)
- Dictionary: person = {"name": "Alice", "age": 25}

3. Control Structures
- If Statement:

     if x > 10:
         print("x is greater than 10")
     

- For Loop:

     for fruit in fruits:
         print(fruit)
     

- While Loop:

     while x < 5:
         x += 1
     

4. Functions
- Define Function:

     def greet(name):
         return f"Hello, {name}!"
     

- Lambda Function: add = lambda a, b: a + b

5. Exception Handling
- Try-Except Block:

     try:
         result = 10 / 0
     except ZeroDivisionError:
         print("Cannot divide by zero.")
     

6. File I/O
- Read File:

     with open('file.txt', 'r') as file:
         content = file.read()
     

- Write File:

     with open('file.txt', 'w') as file:
         file.write("Hello, World!")
     

7. List Comprehensions
- Basic Example: squared = [x**2 for x in range(10)]
- Conditional Comprehension: even_squares = [x**2 for x in range(10) if x % 2 == 0]

8. Modules and Packages
- Import Module: import math
- Import Specific Function: from math import sqrt

9. Common Libraries
- NumPy: import numpy as np
- Pandas: import pandas as pd
- Matplotlib: import matplotlib.pyplot as plt

10. Object-Oriented Programming
- Define Class:

      class Dog:
          def __init__(self, name):
              self.name = name
          def bark(self):
              return "Woof!"
      

11. Virtual Environments
- Create Environment: python -m venv myenv
- Activate Environment:
- Windows: myenv\Scripts\activate
- macOS/Linux: source myenv/bin/activate

12. Common Commands
- Run Script: python script.py
- Install Package: pip install package_name
- List Installed Packages: pip list

This Python checklist serves as a quick reference for essential syntax, functions, and best practices to enhance your coding efficiency!

Checklist for Data Analyst: https://dataanalytics.beehiiv.com/p/data

Here you can find essential Python Interview Resources👇
https://t.iss.one/DataSimplifier

Like for more resources like this 👍 ♥️

Share with credits: https://t.iss.one/sqlspecialist

Hope it helps :)

Web Development Essentials to build modern, responsive websites:

1. HTML (Structure)
Tags, Elements, and Attributes
Headings, Paragraphs, Lists
Forms, Inputs, Buttons
Images, Videos, Links
Semantic HTML: <header>, <nav>, <main>, <footer>

2. CSS (Styling)
Selectors, Properties, and Values
Box Model (margin, padding, border)
Flexbox & Grid Layout
Positioning (static, relative, absolute, fixed, sticky)
Media Queries (Responsive Design)

3. JavaScript (Interactivity)
Variables, Data Types, Operators
Functions, Conditionals, Loops
DOM Manipulation (getElementById, addEventListener)
Events (click, submit, change)
Arrays & Objects

4. Version Control (Git & GitHub)
Initialize repository, clone, commit, push, pull
Branching and merge conflicts
Hosting code on GitHub

5. Responsive Design
Mobile-first approach
Viewport meta tag
Flexbox and CSS Grid for layouts
Using relative units (%, em, rem)

6. Browser Dev Tools
Inspect elements
Console for debugging JavaScript
Network tab for API requests

7. Basic SEO & Accessibility
Title tags, meta descriptions
Alt attributes for images
Proper use of semantic tags

8. Deployment
Hosting on GitHub Pages, Netlify, or Vercel
Domain name basics
Continuous deployment setup

Web Development Resources ⬇️
https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z

React with ❤️ for the detailed explanation