Top 10 Must-Know Coding Concepts every interviewer expects you to know.

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*1. Arrays & Strings – The Basics That Build Everything*

Arrays are ordered collections. Strings are just arrays of characters.

You’ll use them in 90% of coding problems.

Beginner Example: Find the max number in an array, reverse a string, check if it’s a palindrome.

Start with: Leetcode Easy Array Problems


*2. Hashing – Remember Stuff Fast*

What it is: Like a super-efficient locker room. You store and find things instantly using keys.

Real Use-case: Count frequencies, detect duplicates, group similar data.

Example: Check if two strings are anagrams.

Use: HashMap or Dictionary in Python


*3. Recursion – When Functions Call Themselves*

What it is: A function solving a smaller version of the same problem.

Looks Scary? It’s not. Think of solving a puzzle by solving one piece at a time.

Example: Factorial, Fibonacci numbers.

Golden Rule: Always define a base case, or it loops forever!


*4. Backtracking – Trial & Error, Smartly Done*

What it is: Try all possible options, but drop paths that don’t work early.

Real World Analogy: Like navigating a maze – go back if you hit a wall.

Example: Sudoku Solver, N-Queens Problem


*5. Dynamic Programming (DP) – Avoid Repeating Work*

What it is: Break problems into smaller parts and store the result so you don’t repeat it.

Example: Fibonacci using DP instead of recursion (faster!)


*6. Sliding Window – Efficient Way to Check Patterns in a Row*

What it is: Instead of checking every combination, move a “window” across the array to find answers.

Example: Find max sum of subarray of size K.

Great for string and array problems.


*7. Trees – Hierarchical Data You Must Understand*

What it is: Like a family tree. Each node can have children.

Key Terms: Root, Leaf, Binary Tree, BST

Why it’s asked: Real apps like file systems, websites use trees.

Example: Inorder/Preorder/Postorder Traversals


*8. Graphs – Networks of Connections*

What it is: Nodes connected by edges. Can go in any direction.

Examples: Maps, social media friends, recommendation engines

Learn: BFS (Breadth-First Search), DFS (Depth-First Search)


*9. Greedy – Pick Best at Every Step (Fast but Risky)*

What it is: Make the best local choice hoping it leads to the global best.

Good For Simple optimization problems

Example: Activity Selection, Coin Change (with greedy strategy)


*10. Bit Manipulation – Play with 0s and 1s*

What it is: Perform operations directly on binary representations. It’s super fast and memory-efficient

Example: Check if a number is a power of 2, find the only non-repeating element


What to Do Next (Action Plan):

- Start with Arrays, then move to Hashing

- Try Recursion + Backtracking next

- Once comfy, go into DP, Graphs, and Trees

- Use platforms like Leetcode (easy → medium), GeeksforGeeks, or Neetcode

If this helped, drop a ❤️ and share with your coding gang.

Programming Resources: 👇 https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17

Here are 10 popular programming languages based on versatile, widely-used, and in-demand languages:
1. Python – Ideal for beginners and professionals; used in web development, data analysis, AI, and more.

2. Java – A classic language for building enterprise applications, Android apps, and large-scale systems.

3. C – The foundation for many other languages; great for understanding low-level programming concepts.

4. C++ – Popular for game development, competitive programming, and performance-critical applications.

5. C# – Widely used for Windows applications, game development (Unity), and enterprise software.

6. Go (Golang) – A modern language designed for performance and scalability, popular in cloud services.

7. Rust – Known for its safety and performance, ideal for system-level programming.

8. Kotlin – The preferred language for Android development with modern features.

9. Swift – Used for developing iOS and macOS applications with simplicity and power.

10. PHP – A staple for web development, powering many websites and applications

When to Use Which Programming Language?

C ➝ OS Development, Embedded Systems, Game Engines
C++ ➝ Game Dev, High-Performance Apps, Finance
Java ➝ Enterprise Apps, Android, Backend
C# ➝ Unity Games, Windows Apps
Python ➝ AI/ML, Data, Automation, Web Dev
JavaScript ➝ Frontend, Full-Stack, Web Games
Golang ➝ Cloud Services, APIs, Networking
Swift ➝ iOS/macOS Apps
Kotlin ➝ Android, Backend
PHP ➝ Web Dev (WordPress, Laravel)
Ruby ➝ Web Dev (Rails), Prototypes
Rust ➝ System Apps, Blockchain, HPC
Lua ➝ Game Scripting (Roblox, WoW)
R ➝ Stats, Data Science, Bioinformatics
SQL ➝ Data Analysis, DB Management
TypeScript ➝ Scalable Web Apps
Node.js ➝ Backend, Real-Time Apps
React ➝ Modern Web UIs
Vue ➝ Lightweight SPAs
Django ➝ AI/ML Backend, Web Dev
Laravel ➝ Full-Stack PHP
Blazor ➝ Web with .NET
Spring Boot ➝ Microservices, Java Enterprise
Ruby on Rails ➝ MVPs, Startups
HTML/CSS ➝ UI/UX, Web Design
Git ➝ Version Control
Linux ➝ Server, Security, DevOps
DevOps ➝ Infra Automation, CI/CD
CI/CD ➝ Testing + Deployment
Docker ➝ Containerization
Kubernetes ➝ Cloud Orchestration
Microservices ➝ Scalable Backends
Selenium ➝ Web Testing
Playwright ➝ Modern Web Automation

Credits: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17

ENJOY LEARNING 👍👍

𝗣𝘆𝘁𝗵𝗼𝗻 𝗟𝗶𝘀𝘁 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁

𝟭. 𝗮𝗽𝗽𝗲𝗻𝗱( ) – Adds an element to the end of the list.
𝟮. 𝗰𝗼𝘂𝗻𝘁( ) – Returns the number of occurrences of a specific element.
𝟯. 𝗰𝗼𝗽𝘆( ) – Creates a duplicate of the list.
𝟰. 𝗶𝗻𝗱𝗲𝘅( ) – Returns the position of the first occurrence of an element.
𝟱. 𝗶𝗻𝘀𝗲𝗿𝘁(𝟭, ) – Inserts an element at a specified index.
𝟲. 𝗿𝗲𝘃𝗲𝗿𝘀𝗲( ) – Reverses the order of elements in the list.
𝟳. 𝗽𝗼𝗽( ) – Removes and returns the last element.
𝟴. 𝗰𝗹𝗲𝗮𝗿( ) – Removes all elements from the list.
𝟵. 𝗽𝗼𝗽(𝟭) – Removes and returns the element at index 1.

Master these list methods to handle Python lists efficiently! 🚀

Top 10 Python Concepts
Variables & Data Types

Understand integers, floats, strings, booleans, lists, tuples, sets, and dictionaries.

Control Flow (if, else, elif)
Write logic-based programs using conditional statements.

Loops (for & while)
Automate tasks and iterate over data efficiently.

Functions
Build reusable code blocks with def, understand parameters, return values, and scope.

List Comprehensions
Create and transform lists concisely:
[x*2 for x in range(10) if x % 2 == 0]

Modules & Packages
Import built-in, third-party, or custom modules to structure your code.

Exception Handling
Handle errors using try, except, finally for robust programs.

Object-Oriented Programming (OOP)
Learn classes, objects, inheritance, encapsulation, and polymorphism.

File Handling
Open, read, write, and manage files using open(), read(), write().

Working with Libraries
Use powerful libraries like:
- NumPy for numerical operations
- Pandas for data analysis
- Matplotlib/Seaborn for visualization
- Requests for API calls
- JSON for data parsing

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