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Tips for solving leetcode codings interview problems

If input array is sorted then
- Binary search
- Two pointers

If asked for all permutations/subsets then
- Backtracking

If given a tree then
- DFS
- BFS

If given a graph then
- DFS
- BFS

If given a linked list then
- Two pointers

If recursion is banned then
- Stack

If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer

If asked for maximum/minimum subarray/subset/options then
- Dynamic programming

If asked for top/least K items then
- Heap

If asked for common strings then
- Map
- Trie

Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space

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The Only SQL You Actually Need For Your First Job (Data Analytics)

The Learning Trap: What Most Beginners Fall Into

When starting out, it's common to feel like you need to master every possible SQL concept. You binge YouTube videos, tutorials, and courses, yet still feel lost in interviews or when given a real dataset.

Common traps:

- Complex subqueries

- Advanced CTEs

- Recursive queries

- 100+ tutorials watched

- 0 practical experience

Reality Check: What You'll Actually Use 75% of the Time

Most data analytics roles (especially entry-level) require clarity, speed, and confidence with core SQL operations. Here’s what covers most daily work:

1. SELECT, FROM, WHERE — The Foundation

SELECT name, age
FROM employees
WHERE department = 'Finance';

This is how almost every query begins. Whether exploring a dataset or building a dashboard, these are always in use.

2. JOINs — Combining Data From Multiple Tables

SELECT e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.id;

You’ll often join tables like employee data with department, customer orders with payments, etc.

3. GROUP BY — Summarizing Data

SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department;

Used to get summaries by categories like sales per region or users by plan.

4. ORDER BY — Sorting Results

SELECT name, salary
FROM employees
ORDER BY salary DESC;

Helps sort output for dashboards or reports.

5. Aggregations — Simple But Powerful

Common functions: COUNT(), SUM(), AVG(), MIN(), MAX()

SELECT AVG(salary)
FROM employees
WHERE department = 'IT';

Gives quick insights like average deal size or total revenue.

6. ROW_NUMBER() — Adding Row Logic

SELECT *
FROM (
SELECT *, ROW_NUMBER() OVER(PARTITION BY customer_id ORDER BY order_date DESC) as rn
FROM orders
) sub
WHERE rn = 1;

Used for deduplication, rankings, or selecting the latest record per group.

Credits: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02

React ❤️ for more

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Don't overwhelm to learn JavaScript, JavaScript is only this much

1.Variables
• var
• let
• const

2. Data Types
• number
• string
• boolean
• null
• undefined
• symbol

3.Declaring variables
• var
• let
• const

4.Expressions
Primary expressions
• this
• Literals
• []
• {}
• function
• class
• function*
• async function
• async function*
• /ab+c/i
• string
• ( )

Left-hand-side expressions
• Property accessors
• ?.
• new
• new .target
• import.iss.oneta
• super
• import()

5.operators
• Arithmetic Operators: +, -, *, /, %
• Comparison Operators: ==, ===, !=, !==, <, >, <=, >=
• Logical Operators: &&, ||, !

6.Control Structures
• if
• else if
• else
• switch
• case
• default

7.Iterations/Loop
• do...while
• for
• for...in
• for...of
• for await...of
• while

8.Functions
• Arrow Functions
• Default parameters
• Rest parameters
• arguments
• Method definitions
• getter
• setter

9.Objects and Arrays
• Object Literal: { key: value }
• Array Literal: [element1, element2, ...]
• Object Methods and Properties
• Array Methods: push(), pop(), shift(), unshift(),
splice(), slice(), forEach(), map(), filter()

10.Classes and Prototypes
• Class Declaration
• Constructor Functions
• Prototypal Inheritance
• extends keyword
• super keyword
• Private class features
• Public class fields
• static
• Static initialization blocks

11.Error Handling
• try,
• catch,
• finally (exception handling)

ADVANCED CONCEPTS

12.Closures
• Lexical Scope
• Function Scope
• Closure Use Cases

13.Asynchronous JavaScript
• Callback Functions
• Promises
• async/await Syntax
• Fetch API
• XMLHttpRequest

14.Modules
• import and export Statements (ES6 Modules)
• CommonJS Modules (require, module.exports)

15.Event Handling
• Event Listeners
• Event Object
• Bubbling and Capturing

16.DOM Manipulation
• Selecting DOM Elements
• Modifying Element Properties
• Creating and Appending Elements

17.Regular Expressions
• Pattern Matching
• RegExp Methods: test(), exec(), match(), replace()

18.Browser APIs
• localStorage and sessionStorage
• navigator Object
• Geolocation API
• Canvas API

19.Web APIs
• setTimeout(), setInterval()
• XMLHttpRequest
• Fetch API
• WebSockets

20.Functional Programming
• Higher-Order Functions
• map(), reduce(), filter()
• Pure Functions and Immutability

21.Promises and Asynchronous Patterns
• Promise Chaining
• Error Handling with Promises
• Async/Await

22.ES6+ Features
• Template Literals
• Destructuring Assignment
• Rest and Spread Operators
• Arrow Functions
• Classes and Inheritance
• Default Parameters
• let, const Block Scoping

23.Browser Object Model (BOM)
• window Object
• history Object
• location Object
• navigator Object

24.Node.js Specific Concepts
• require()
• Node.js Modules (module.exports)
• File System Module (fs)
• npm (Node Package Manager)

25.Testing Frameworks
• Jasmine
• Mocha
• Jest

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Skills to become a successful web developer💯👨🏻‍💻

1. HTML/CSS Basics 📄🎨
Master the building blocks of the web.

2. JavaScript 💻⚡
Add interactivity and dynamic content to your sites.

3. Responsive Design 📱🌍
Ensure your sites look great on all devices!

4. Version Control (Git) 🛠️🔄
Track changes and collaborate with ease.

5. Frameworks (React, Angular, etc) 🚀🛠️
Speed up development with powerful tools.

6. Backend Languages (Node.js, Python, etc)🐍💻
Handle server-side logic and databases.

7. APIs 🔗📡
Connect and integrate with other services.

8. Problem-Solving Skills 🧩🤔
Tackle challenges creatively and efficiently.

9. Testing/Debugging 🔍🐞
Ensure your code runs smoothly and bug-free.

10. Soft Skills (Communication, Teamwork) 🗣️🤝
Work effectively with others and convey ideas clearly.

11. Continuous Learning 📚✨
Stay updated with the latest technologies and trends.

Web Development Best Resources: https://topmate.io/coding/930165

ENJOY LEARNING 👍👍

#webdev

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SQL CHEAT SHEET👩‍💻

Here is a quick cheat sheet of some of the most essential SQL commands:

SELECT - Retrieves data from a database

UPDATE - Updates existing data in a database

DELETE - Removes data from a database

INSERT - Adds data to a database

CREATE - Creates an object such as a database or table

ALTER - Modifies an existing object in a database

DROP -Deletes an entire table or database

ORDER BY - Sorts the selected data in an ascending or descending order

WHERE – Condition used to filter a specific set of records from the database

GROUP BY - Groups a set of data by a common parameter

HAVING - Allows the use of aggregate functions within the query

JOIN - Joins two or more tables together to retrieve data

INDEX - Creates an index on a table, to speed up search times.

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SQL Joins ✅

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I’ve never met an awesome software developer who:
- Thought learning new frameworks was a waste.
- Avoided refactoring because “it already works.”
- Avoided debugging because it was frustrating.
- Never deleted code they once proudly wrote.
- Never pushed code that broke in production.
- Stuck to one programming language forever.
- Stopped learning after getting their first job.
- Didn’t rewrite their code later.
- Only worked on projects that felt safe.
- Refused to ask questions when stuck.

Great developers aren’t perfect.

They take risks.
They make mistakes.
They debug endlessly.
They make wrong estimates.

But during all that, They learn.

And that’s exactly why they grow.

Keep that in mind

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Theoretical Questions for Coding Interviews on Basic Data Structures

1. What is a Data Structure?
A data structure is a way of organizing and storing data so that it can be accessed and modified efficiently. Common data structures include arrays, linked lists, stacks, queues, and trees.

2. What is an Array?
An array is a collection of elements, each identified by an index. It has a fixed size and stores elements of the same type in contiguous memory locations.

3. What is a Linked List?
A linked list is a linear data structure where elements (nodes) are stored non-contiguously. Each node contains a value and a reference (or link) to the next node. Unlike arrays, linked lists can grow dynamically.

4. What is a Stack?
A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. The most recently added element is the first one to be removed. Common operations include push (add an element) and pop (remove an element).

5. What is a Queue?
A queue is a linear data structure that follows the First In, First Out (FIFO) principle. The first element added is the first one to be removed. Common operations include enqueue (add an element) and dequeue (remove an element).

6. What is a Binary Tree?
A binary tree is a hierarchical data structure where each node has at most two children, usually referred to as the left and right child. It is used for efficient searching and sorting.

7. What is the difference between an array and a linked list?

Array: Fixed size, elements stored in contiguous memory.

Linked List: Dynamic size, elements stored non-contiguously, each node points to the next.

8. What is the time complexity for accessing an element in an array vs. a linked list?

Array: O(1) for direct access by index.

Linked List: O(n) for access, as you must traverse the list from the start to find an element.

9. What is the time complexity for inserting or deleting an element in an array vs. a linked list?

Array:

Insertion/Deletion at the end: O(1).

Insertion/Deletion at the beginning or middle: O(n) because elements must be shifted.

Linked List:

Insertion/Deletion at the beginning: O(1).

Insertion/Deletion in the middle or end: O(n), as you need to traverse the list.

10. What is a HashMap (or Dictionary)?
A HashMap is a data structure that stores key-value pairs. It allows efficient lookups, insertions, and deletions using a hash function to map keys to values. Average time complexity for these operations is O(1).

Coding interview: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X

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🔰 How Python Works?

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🧿 Essential React Hooks Part 1

Each hook addresses specific performance, state management, or accessibility needs within React components, allowing for efficient and organized code structure.

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