Top 7 Must-Prepare Topics for Coding Interviews (2025 Edition)
✅ Arrays & Strings – Master problems on rotation, sliding window, two pointers, etc.
✅ Linked Lists – Practice reversal, cycle detection, and merging lists
✅ Hashing & Maps – Use hash tables for fast lookups and frequency-based problems
✅ Recursion & Backtracking – Solve problems like permutations, subsets, and Sudoku
✅ Dynamic Programming – Understand memoization, tabulation, and classic patterns
✅ Trees & Graphs – Cover traversal (BFS/DFS), shortest paths, and tree operations
✅ Stacks & Queues – Solve problems involving monotonic stacks, parentheses, and sliding windows
These are the essentials to crack FAANG-level interviews or product-based companies.
React with ❤️ for detailed explanation on each topic
✅ Arrays & Strings – Master problems on rotation, sliding window, two pointers, etc.
✅ Linked Lists – Practice reversal, cycle detection, and merging lists
✅ Hashing & Maps – Use hash tables for fast lookups and frequency-based problems
✅ Recursion & Backtracking – Solve problems like permutations, subsets, and Sudoku
✅ Dynamic Programming – Understand memoization, tabulation, and classic patterns
✅ Trees & Graphs – Cover traversal (BFS/DFS), shortest paths, and tree operations
✅ Stacks & Queues – Solve problems involving monotonic stacks, parentheses, and sliding windows
These are the essentials to crack FAANG-level interviews or product-based companies.
React with ❤️ for detailed explanation on each topic
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The Secret to learn SQL:
It's not about knowing everything
It's about doing simple things well
What You ACTUALLY Need:
1. SELECT Mastery
* SELECT * LIMIT 10
(yes, for exploration only!)
* COUNT, SUM, AVG
(used every single day)
* Basic DATE functions
(life-saving for reports)
* CASE WHEN
2. JOIN Logic
* LEFT JOIN
(your best friend)
* INNER JOIN
(your second best friend)
* That's it.
3. WHERE Magic
* Basic conditions
* AND, OR operators
* IN, NOT IN
* NULL handling
* LIKE for text search
4. GROUP BY Essentials
* Basic grouping
* HAVING clause
* Multiple columns
* Simple aggregations
Most common tasks:
* Pull monthly sales
* Count unique customers
* Calculate basic metrics
* Filter date ranges
* Join 2-3 tables
Focus on:
* Clean code
* Clear comments
* Consistent formatting
* Proper indentation
Here you can find essential SQL Interview Resources👇
https://t.iss.one/mysqldata
Like this post if you need more 👍❤️
Hope it helps :)
#sql
It's not about knowing everything
It's about doing simple things well
What You ACTUALLY Need:
1. SELECT Mastery
* SELECT * LIMIT 10
(yes, for exploration only!)
* COUNT, SUM, AVG
(used every single day)
* Basic DATE functions
(life-saving for reports)
* CASE WHEN
2. JOIN Logic
* LEFT JOIN
(your best friend)
* INNER JOIN
(your second best friend)
* That's it.
3. WHERE Magic
* Basic conditions
* AND, OR operators
* IN, NOT IN
* NULL handling
* LIKE for text search
4. GROUP BY Essentials
* Basic grouping
* HAVING clause
* Multiple columns
* Simple aggregations
Most common tasks:
* Pull monthly sales
* Count unique customers
* Calculate basic metrics
* Filter date ranges
* Join 2-3 tables
Focus on:
* Clean code
* Clear comments
* Consistent formatting
* Proper indentation
Here you can find essential SQL Interview Resources👇
https://t.iss.one/mysqldata
Like this post if you need more 👍❤️
Hope it helps :)
#sql
❤5
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C++ Programming Roadmap
|
|-- Fundamentals
| |-- Basics of Programming
| | |-- Introduction to C++
| | |-- Setting Up Development Environment (IDE: Code::Blocks, Visual Studio, etc.)
| | |-- Compiling and Running C++ Programs
| |
| |-- Syntax and Structure
| | |-- Basic Syntax
| | |-- Variables and Data Types
| | |-- Operators (Arithmetic, Relational, Logical, Bitwise)
|
|-- Control Structures
| |-- Conditional Statements
| | |-- If-Else Statements
| | |-- Switch Case
| |
| |-- Loops
| | |-- For Loop
| | |-- While Loop
| | |-- Do-While Loop
| |
| |-- Jump Statements
| | |-- Break, Continue
| | |-- Goto Statement
|
|-- Functions and Scope
| |-- Defining Functions
| | |-- Function Syntax
| | |-- Parameters and Arguments (Pass by Value, Pass by Reference)
| | |-- Return Statement
| |
| |-- Function Overloading
| | |-- Overloading Functions with Different Parameters
| |
| |-- Scope and Lifetime
| | |-- Local and Global Scope
| | |-- Static Variables
|
|-- Object-Oriented Programming (OOP)
| |-- Basics of OOP
| | |-- Classes and Objects
| | |-- Member Functions and Data Members
| |
| |-- Constructors and Destructors
| | |-- Constructor Types (Default, Parameterized, Copy)
| | |-- Destructor Basics
| |
| |-- Inheritance
| | |-- Single and Multiple Inheritance
| | |-- Protected Access Specifier
| | |-- Virtual Base Class
| |
| |-- Polymorphism
| | |-- Function Overriding
| | |-- Virtual Functions and Pure Virtual Functions
| | |-- Abstract Classes
| |
| |-- Encapsulation and Abstraction
| | |-- Access Specifiers (Public, Private, Protected)
| | |-- Getters and Setters
| |
| |-- Operator Overloading
| | |-- Overloading Operators (Arithmetic, Relational, etc.)
| | |-- Friend Functions
|
|-- Advanced C++
| |-- Pointers and Dynamic Memory
| | |-- Pointer Basics
| | |-- Dynamic Memory Allocation (new, delete)
| | |-- Pointer Arithmetic
| |
| |-- References
| | |-- Reference Variables
| | |-- Passing by Reference
| |
| |-- Templates
| | |-- Function Templates
| | |-- Class Templates
| |
| |-- Exception Handling
| | |-- Try-Catch Blocks
| | |-- Throwing Exceptions
| | |-- Standard Exceptions
|
|-- Data Structures
| |-- Arrays and Strings
| | |-- One-Dimensional and Multi-Dimensional Arrays
| | |-- String Handling
| |
| |-- Linked Lists
| | |-- Singly and Doubly Linked Lists
| |
| |-- Stacks and Queues
| | |-- Stack Operations (Push, Pop, Peek)
| | |-- Queue Operations (Enqueue, Dequeue)
| |
| |-- Trees and Graphs
| | |-- Binary Trees, Binary Search Trees
| | |-- Graph Representation and Traversal (DFS, BFS)
|
|-- Standard Template Library (STL)
| |-- Containers
| | |-- Vectors, Lists, Deques
| | |-- Stacks, Queues, Priority Queues
| | |-- Sets, Maps, Unordered Maps
| |
| |-- Iterators
| | |-- Input and Output Iterators
| | |-- Forward, Bidirectional, and Random Access Iterators
| |
| |-- Algorithms
| | |-- Sorting, Searching, and Manipulation
| | |-- Numeric Algorithms
|
|-- File Handling
| |-- Streams and File I/O
| | |-- ifstream, ofstream, fstream
| | |-- Reading and Writing Files
| | |-- Binary File Handling
|
|-- Testing and Debugging
| |-- Debugging Tools
| | |-- gdb (GNU Debugger)
| | |-- Valgrind for Memory Leak Detection
| |
| |-- Unit Testing
| | |-- Google Test (gtest)
| | |-- Writing and Running Tests
|
|-- Deployment and DevOps
| |-- Version Control with Git
| | |-- Integrating C++ Projects with GitHub
| |-- Continuous Integration/Continuous Deployment (CI/CD)
| | |-- Using Jenkins or GitHub
Join @free4unow_backup for more free resources
ENJOY LEARNING 👍👍
|
|-- Fundamentals
| |-- Basics of Programming
| | |-- Introduction to C++
| | |-- Setting Up Development Environment (IDE: Code::Blocks, Visual Studio, etc.)
| | |-- Compiling and Running C++ Programs
| |
| |-- Syntax and Structure
| | |-- Basic Syntax
| | |-- Variables and Data Types
| | |-- Operators (Arithmetic, Relational, Logical, Bitwise)
|
|-- Control Structures
| |-- Conditional Statements
| | |-- If-Else Statements
| | |-- Switch Case
| |
| |-- Loops
| | |-- For Loop
| | |-- While Loop
| | |-- Do-While Loop
| |
| |-- Jump Statements
| | |-- Break, Continue
| | |-- Goto Statement
|
|-- Functions and Scope
| |-- Defining Functions
| | |-- Function Syntax
| | |-- Parameters and Arguments (Pass by Value, Pass by Reference)
| | |-- Return Statement
| |
| |-- Function Overloading
| | |-- Overloading Functions with Different Parameters
| |
| |-- Scope and Lifetime
| | |-- Local and Global Scope
| | |-- Static Variables
|
|-- Object-Oriented Programming (OOP)
| |-- Basics of OOP
| | |-- Classes and Objects
| | |-- Member Functions and Data Members
| |
| |-- Constructors and Destructors
| | |-- Constructor Types (Default, Parameterized, Copy)
| | |-- Destructor Basics
| |
| |-- Inheritance
| | |-- Single and Multiple Inheritance
| | |-- Protected Access Specifier
| | |-- Virtual Base Class
| |
| |-- Polymorphism
| | |-- Function Overriding
| | |-- Virtual Functions and Pure Virtual Functions
| | |-- Abstract Classes
| |
| |-- Encapsulation and Abstraction
| | |-- Access Specifiers (Public, Private, Protected)
| | |-- Getters and Setters
| |
| |-- Operator Overloading
| | |-- Overloading Operators (Arithmetic, Relational, etc.)
| | |-- Friend Functions
|
|-- Advanced C++
| |-- Pointers and Dynamic Memory
| | |-- Pointer Basics
| | |-- Dynamic Memory Allocation (new, delete)
| | |-- Pointer Arithmetic
| |
| |-- References
| | |-- Reference Variables
| | |-- Passing by Reference
| |
| |-- Templates
| | |-- Function Templates
| | |-- Class Templates
| |
| |-- Exception Handling
| | |-- Try-Catch Blocks
| | |-- Throwing Exceptions
| | |-- Standard Exceptions
|
|-- Data Structures
| |-- Arrays and Strings
| | |-- One-Dimensional and Multi-Dimensional Arrays
| | |-- String Handling
| |
| |-- Linked Lists
| | |-- Singly and Doubly Linked Lists
| |
| |-- Stacks and Queues
| | |-- Stack Operations (Push, Pop, Peek)
| | |-- Queue Operations (Enqueue, Dequeue)
| |
| |-- Trees and Graphs
| | |-- Binary Trees, Binary Search Trees
| | |-- Graph Representation and Traversal (DFS, BFS)
|
|-- Standard Template Library (STL)
| |-- Containers
| | |-- Vectors, Lists, Deques
| | |-- Stacks, Queues, Priority Queues
| | |-- Sets, Maps, Unordered Maps
| |
| |-- Iterators
| | |-- Input and Output Iterators
| | |-- Forward, Bidirectional, and Random Access Iterators
| |
| |-- Algorithms
| | |-- Sorting, Searching, and Manipulation
| | |-- Numeric Algorithms
|
|-- File Handling
| |-- Streams and File I/O
| | |-- ifstream, ofstream, fstream
| | |-- Reading and Writing Files
| | |-- Binary File Handling
|
|-- Testing and Debugging
| |-- Debugging Tools
| | |-- gdb (GNU Debugger)
| | |-- Valgrind for Memory Leak Detection
| |
| |-- Unit Testing
| | |-- Google Test (gtest)
| | |-- Writing and Running Tests
|
|-- Deployment and DevOps
| |-- Version Control with Git
| | |-- Integrating C++ Projects with GitHub
| |-- Continuous Integration/Continuous Deployment (CI/CD)
| | |-- Using Jenkins or GitHub
Join @free4unow_backup for more free resources
ENJOY LEARNING 👍👍
❤2👍1
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✅ Detailed Roadmap to Become a Programmer
📂 Learn Programming Fundamentals
Start with basics like programming logic, syntax, and how code flows. This builds your foundation.
∟📂 Choose a Language
Pick one popular language like Python (easy & versatile), Java (widely used in big systems), or C++ (great for performance). Focus on mastering it first.
∟📂 Learn Data Structures & Algorithms
Understand arrays, lists, trees, sorting, searching — these help write efficient code and solve complex problems.
∟📂 Learn Problem Solving
Practice coding challenges on platforms like LeetCode or HackerRank to improve your logic and speed.
∟📂 Learn OOPs & Design Patterns
Object-Oriented Programming (OOP) teaches how to structure code; design patterns show reusable solutions to common problems.
∟📂 Learn Version Control (Git & GitHub)
Essential for collaboration—track your code changes and work with others safely using Git and GitHub.
∟📂 Learn Debugging & Testing
Find and fix bugs; test your code to make sure it works as expected.
∟📂 Work on Real-World Projects
Build practical projects to apply what you learned and showcase skills to employers.
∟📂 Contribute to Open Source
Collaborate on existing projects—gain experience, community recognition, and improve your coding.
∟✅ Apply for Job / Internship
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👍 React ♥️ for more
📂 Learn Programming Fundamentals
Start with basics like programming logic, syntax, and how code flows. This builds your foundation.
∟📂 Choose a Language
Pick one popular language like Python (easy & versatile), Java (widely used in big systems), or C++ (great for performance). Focus on mastering it first.
∟📂 Learn Data Structures & Algorithms
Understand arrays, lists, trees, sorting, searching — these help write efficient code and solve complex problems.
∟📂 Learn Problem Solving
Practice coding challenges on platforms like LeetCode or HackerRank to improve your logic and speed.
∟📂 Learn OOPs & Design Patterns
Object-Oriented Programming (OOP) teaches how to structure code; design patterns show reusable solutions to common problems.
∟📂 Learn Version Control (Git & GitHub)
Essential for collaboration—track your code changes and work with others safely using Git and GitHub.
∟📂 Learn Debugging & Testing
Find and fix bugs; test your code to make sure it works as expected.
∟📂 Work on Real-World Projects
Build practical projects to apply what you learned and showcase skills to employers.
∟📂 Contribute to Open Source
Collaborate on existing projects—gain experience, community recognition, and improve your coding.
∟✅ Apply for Job / Internship
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Data Analytics Pattern Identification....;;
Trend Analysis: Examining data over time to identify upward or downward trends.
Seasonal Patterns: Identifying recurring patterns or trends based on seasons or specific time periods
Correlation: Understanding relationships between variables and how changes in one may affect another.
Outlier Detection: Identifying data points that deviate significantly from the overall pattern.
Clustering: Grouping similar data points together to find natural patterns within the data.
Classification: Categorizing data into predefined classes or groups based on certain features.
Regression Analysis: Predicting a dependent variable based on the values of independent variables.
Frequency Distribution: Analyzing the distribution of values within a dataset.
Pattern Recognition: Identifying recurring structures or shapes within the data.
Text Analysis: Extracting insights from unstructured text data through techniques like sentiment analysis or topic modeling.
These patterns help organizations make informed decisions, optimize processes, and gain a deeper understanding of their data.
Trend Analysis: Examining data over time to identify upward or downward trends.
Seasonal Patterns: Identifying recurring patterns or trends based on seasons or specific time periods
Correlation: Understanding relationships between variables and how changes in one may affect another.
Outlier Detection: Identifying data points that deviate significantly from the overall pattern.
Clustering: Grouping similar data points together to find natural patterns within the data.
Classification: Categorizing data into predefined classes or groups based on certain features.
Regression Analysis: Predicting a dependent variable based on the values of independent variables.
Frequency Distribution: Analyzing the distribution of values within a dataset.
Pattern Recognition: Identifying recurring structures or shapes within the data.
Text Analysis: Extracting insights from unstructured text data through techniques like sentiment analysis or topic modeling.
These patterns help organizations make informed decisions, optimize processes, and gain a deeper understanding of their data.
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