JavaScript (JS) roadmap:

1. Basic Fundamentals:
   - Variables, data types, and operators.
   - Control structures like loops and conditionals.
   - Functions and scope.

2. DOM Manipulation:
   - Access and modify HTML and CSS using JavaScript.
   - Event handling.

3. Asynchronous Programming:
   - Promises and async/await for handling asynchronous operations.

4. ES6 and Modern JavaScript:
   - Arrow functions, template literals, and destructuring.
   - Modules for code organization.
   - Classes for object-oriented programming.

5. Popular Libraries and Frameworks:
   - Learn libraries like jQuery or frameworks like React, Angular, or Vue depending on your project needs.

6. Package Management:
   - Tools like npm or yarn for managing dependencies.

7. Build Tools:
   - Webpack, Babel, and other tools for bundling and transpiling.

8. API Interaction:
   - Fetch or Axios for making API requests.

9. State Management (For Frameworks):
   - Redux for React, Vuex for Vue, etc.

10. Testing:
    - Learn testing frameworks like Jest.

11. Version Control:
    - Git for code versioning and collaboration.

12. Continuous Integration (CI) and Deployment:
    - Travis CI, Jenkins, or others for automating testing and deployment.

13. Server-Side JavaScript (Optional):
    - Node.js for server-side development.

14. Advanced Topics (Optional):
    - WebSockets, WebRTC, Progressive Web Apps (PWAs), and more.

This roadmap covers the foundational knowledge and key steps in a JavaScript developer's journey. You can explore more deeply into areas that align with your specific goals and projects.

Learning DSA wasn’t just about acing interviews, --- it was about thinking better, building faster, and debugging smarter.

🎯 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟵 𝗰𝗼𝗿𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝘁𝗵𝗮𝘁 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗱 𝗵𝗼𝘄 𝗜 𝘀𝗼𝗹𝘃𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀:
• Sliding Windows
• Two Pointers
• Stack Based Patterns
• Dynamic Programing
• BFS/DFS (Trees & Graphs)
• Merge Intervals
• Backtracking & Subsets
• top-k Elements (Heaps)
• Greedy Techniques


🛤️ 𝗠𝘆 𝗣𝗮𝘁𝗵 𝘁𝗼 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗗𝗦𝗔:
• Started with basic problems on arrays & strings
• Solved 1-2 problems a day, consistently for 3 months
• Focused more on patterns than individual questions
• Made my own notes, revisited problems I struggled with
• Used visual tools to understand recursion & DP
• Practiced explaining my solutions out loud (like system design reviews)
• Applied patterns in real-world projects (DevOps automation, log parsing, infra tools)


💡 𝗟𝗼𝗼𝗸𝗶𝗻𝗴 𝗯𝗮𝗰𝗸, 𝗼𝗻𝗲 𝘁𝗵𝗶𝗻𝗴 𝗶𝘀 𝗰𝗹𝗲𝗮𝗿:
> It's not how many problems you solve, it's how well you can recognize the pattern hiding in each one.

You can find more free resources on my WhatsApp channel: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17

Useful Run Commands Every Windows User Should Know

Press Win + R on your ⌨️ to open the Run dialog box and enter any of 👇 commands to access the respective tool.

🔹 "." -  the user's folder.
🔹 ".." - user folder.
🔹 "control" - control panel.
🔹 "msconfig" - system configuration parameters.
🔹 "appwiz.cpl" - programs and components.
🔹 "cleanmgr" - a disk cleaning utility.
🔹 "resmon" - resource monitor.
🔹 "calc", "notepad", "mspaint" - calculator, notepad and paint.
🔹 "main.cpl" - mouse parameters.
🔹 "mstsc" - remote desktop.
🔹 "msinfo32" - system information.
🔹 wab  - Contacts.
🔹 dccw - Display Color Calibration.
🔹 desk.cpl - Display Settings.

➡️ Give Reactions 🤟

Here's a short roadmap to crack an IT job with a non-CS background 🚀

1. 📚 Learn basics of CS and programming.
2. 🎯 Choose a specialization (e.g., web dev, data analysis).
3. 🏆 Complete online courses and certifications.
4. 🛠️ Build a portfolio of projects.
5. 🤝 Network with professionals.
6. 💼 Seek internships for experience.
7. 📚 Keep learning and stay updated.
8. 🧠 Develop soft skills.
9. 📝 Prepare for interviews.
10. 💪 Stay persistent and positive! Good luck!


React to This Message so I share Content like this ❤️

Interview Coding Patterns

We'll cover multiple patterns asked in coding interviews. These patterns help you recognize how to approach different types of coding problems smartly — instead of solving each from scratch.

We’ll divide this into multiple parts — starting from basic and gradually going toward advanced.

Here's what we’ll cover in this section:

1. Stock Buy & Sell (Single Transaction)
2. Stock Buy & Sell (Multiple Transactions)
3. Kadane’s Algorithm (Max Subarray)
4. Sliding Window (Fixed + Variable Size)
5. Two Pointer Technique
6. Prefix Sum
7. HashMap-Based Pattern
8. Binary Search Variants
9. Backtracking Basics
10. Recursion to DP Conversion
11. Sorting-Based Tricks
12. Greedy Patterns
13. Frequency Maps and Counters
14. Stacks and Queues Based Patterns
15. Substring & Subarray Techniques

Access it for free here
👇👇
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1629

Coding Resources 👆

30-days learning plan to master Data Structures and Algorithms (DSA) and prepare for coding interviews.

### Week 1: Foundations and Basic Data Structures

Day 1-3: Arrays and Strings
- Topics to Cover:
- Array basics, operations (insertion, deletion, searching)
- String manipulation
- Two-pointer technique, sliding window technique
- Practice Problems:
- Two Sum
- Maximum Subarray
- Reverse a String
- Longest Substring Without Repeating Characters

Day 4-5: Linked Lists
- Topics to Cover:
- Singly linked list, doubly linked list, circular linked list
- Common operations (insertion, deletion, reversal)
- Practice Problems:
- Reverse a Linked List
- Merge Two Sorted Lists
- Remove Nth Node From End of List

Day 6-7: Stacks and Queues
- Topics to Cover:
- Stack operations (push, pop, top)
- Queue operations (enqueue, dequeue)
- Applications (expression evaluation, backtracking, breadth-first search)
- Practice Problems:
- Valid Parentheses
- Implement Stack using Queues
- Implement Queue using Stacks

### Week 2: Advanced Data Structures

Day 8-10: Trees
- Topics to Cover:
- Binary Trees, Binary Search Trees (BST)
- Tree traversal (preorder, inorder, postorder, level order)
- Practice Problems:
- Invert Binary Tree
- Validate Binary Search Tree
- Serialize and Deserialize Binary Tree

Day 11-13: Heaps and Priority Queues
- Topics to Cover:
- Binary heap (min-heap, max-heap)
- Heap operations (insert, delete, extract-min/max)
- Applications (heap sort, priority queues)
- Practice Problems:
- Kth Largest Element in an Array
- Top K Frequent Elements
- Find Median from Data Stream

Day 14: Hash Tables
- Topics to Cover:
- Hashing concept, hash functions, collision resolution (chaining, open addressing)
- Applications (caching, counting frequencies)
- Practice Problems:
- Two Sum (using hash map)
- Group Anagrams
- Subarray Sum Equals K

### Week 3: Algorithms

Day 15-17: Sorting and Searching Algorithms
- Topics to Cover:
- Sorting algorithms (quick sort, merge sort, bubble sort, insertion sort)
- Searching algorithms (binary search, linear search)
- Practice Problems:
- Merge Intervals
- Search in Rotated Sorted Array
- Sort Colors
- Find Peak Element

Day 18-20: Recursion and Backtracking
- Topics to Cover:
- Basic recursion, tail recursion
- Backtracking (N-Queens, Sudoku solver)
- Practice Problems:
- Permutations
- Combination Sum
- Subsets
- Word Search

Day 21: Divide and Conquer
- Topics to Cover:
- Basic concept, merge sort, quick sort, binary search
- Practice Problems:
- Median of Two Sorted Arrays
- Pow(x, n)
- Kth Largest Element in an Array (using divide and conquer)
- Maximum Subarray (using divide and conquer)

### Week 4: Graphs and Dynamic Programming

Day 22-24: Graphs
- Topics to Cover:
- Graph representations (adjacency list, adjacency matrix)
- Traversal algorithms (DFS, BFS)
- Shortest path algorithms (Dijkstra's, Bellman-Ford)
- Practice Problems:
- Number of Islands

Day 25-27: Dynamic Programming
- Topics to Cover:
- Basic concept, memoization, tabulation
- Common problems (knapsack, longest common subsequence)
- Practice Problems:
- Longest Increasing Subsequence
- Maximum Product Subarray

Day 28: Advanced Topics and Miscellaneous
- Topics to Cover:
- Bit manipulation
- Greedy algorithms
- Miscellaneous problems (trie, segment tree, disjoint set)
- Practice Problems:
- Single Number
- Decode Ways
- Minimum Spanning Tree

### Week 5: Review and Mock Interviews

Day 29: Review and Weakness Analysis
- Activities:
  - Review topics you found difficult
  - Revisit problems you struggled with

Day 30: Mock Interviews and Practice
- Activities:
  - Conduct mock interviews with a friend or use online platforms
  - Focus on communication and explaining your thought process

Top DSA resources to crack coding interview

👉 GeekforGeeks

👉 Leetcode

👉 DSA Steps

👉 FreeCodeCamp

👉 Coding Interviews

👉 Best DSA Resources

Join for more: https://t.iss.one/free4unow_backup

ENJOY LEARNING 👍👍

Top 4 Python Projects for Beginners

1. To-Do List App: Create a simple to-do list application where users can add, edit, and delete tasks. This project will help you learn about basic data handling and user interface design.

2. Weather App: Build a weather application that allows users to enter a location and see the current weather conditions. This project will introduce you to working with APIs and handling JSON data.

3. Web Scraper: Develop a web scraper that extracts information from a website and saves it to a file or database. This project will teach you about web scraping techniques and data manipulation.

4. Quiz Game: Create a quiz game where users can answer multiple-choice questions and receive a score at the end. This project will help you practice working with functions, loops, and conditional statements in Python.

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 👍👍