When preparing for an SQL project-based interview, the focus typically shifts from theoretical knowledge to practical application. Here are some SQL project-based interview questions that could help assess your problem-solving skills and experience:
1. Database Design and Schema
- Question: Describe a database schema you have designed in a past project. What were the key entities, and how did you establish relationships between them?
- Follow-Up: How did you handle normalization? Did you denormalize any tables for performance reasons?
2. Data Modeling
- Question: How would you model a database for an e-commerce application? What tables would you include, and how would they relate to each other?
- Follow-Up: How would you design the schema to handle scenarios like discount codes, product reviews, and inventory management?
3. Query Optimization
- Question: Can you discuss a time when you optimized an SQL query? What was the original query, and what changes did you make to improve its performance?
- Follow-Up: What tools or techniques did you use to identify and resolve the performance issues?
4. ETL Processes
- Question: Describe an ETL (Extract, Transform, Load) process you have implemented. How did you handle data extraction, transformation, and loading?
- Follow-Up: How did you ensure data quality and consistency during the ETL process?
5. Handling Large Datasets
- Question: In a project where you dealt with large datasets, how did you manage performance and storage issues?
- Follow-Up: What indexing strategies or partitioning techniques did you use?
6. Joins and Subqueries
- Question: Provide an example of a complex query you wrote involving multiple joins and subqueries. What was the business problem you were solving?
- Follow-Up: How did you ensure that the query performed efficiently?
7. Stored Procedures and Functions
- Question: Have you created stored procedures or functions in any of your projects? Can you describe one and explain why you chose to encapsulate the logic in a stored procedure?
- Follow-Up: How did you handle error handling and logging within the stored procedure?
8. Data Integrity and Constraints
- Question: How did you enforce data integrity in your SQL projects? Can you give examples of constraints (e.g., primary keys, foreign keys, unique constraints) you implemented?
- Follow-Up: How did you handle situations where constraints needed to be temporarily disabled or modified?
9. Version Control and Collaboration
- Question: How did you manage database version control in your projects? What tools or practices did you use to ensure collaboration with other developers?
- Follow-Up: How did you handle conflicts or issues arising from multiple developers working on the same database?
10. Data Migration
- Question: Describe a data migration project you worked on. How did you ensure that the migration was successful, and what steps did you take to handle data inconsistencies or errors?
- Follow-Up: How did you test the migration process before moving to the production environment?
11. Security and Permissions
- Question: In your SQL projects, how did you manage database security?
- Follow-Up: How did you handle encryption or sensitive data within the database?
12. Handling Unstructured Data
- Question: Have you worked with unstructured or semi-structured data in an SQL environment?
- Follow-Up: What challenges did you face, and how did you overcome them?
13. Real-Time Data Processing
- Question: Can you describe a project where you handled real-time data processing using SQL? What were the key challenges, and how did you address them?
- Follow-Up: How did you ensure the performance and reliability of the real-time data processing system?
Be prepared to discuss specific examples from your past work and explain your thought process in detail.
Here you can find SQL Interview Resources👇
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
1. Database Design and Schema
- Question: Describe a database schema you have designed in a past project. What were the key entities, and how did you establish relationships between them?
- Follow-Up: How did you handle normalization? Did you denormalize any tables for performance reasons?
2. Data Modeling
- Question: How would you model a database for an e-commerce application? What tables would you include, and how would they relate to each other?
- Follow-Up: How would you design the schema to handle scenarios like discount codes, product reviews, and inventory management?
3. Query Optimization
- Question: Can you discuss a time when you optimized an SQL query? What was the original query, and what changes did you make to improve its performance?
- Follow-Up: What tools or techniques did you use to identify and resolve the performance issues?
4. ETL Processes
- Question: Describe an ETL (Extract, Transform, Load) process you have implemented. How did you handle data extraction, transformation, and loading?
- Follow-Up: How did you ensure data quality and consistency during the ETL process?
5. Handling Large Datasets
- Question: In a project where you dealt with large datasets, how did you manage performance and storage issues?
- Follow-Up: What indexing strategies or partitioning techniques did you use?
6. Joins and Subqueries
- Question: Provide an example of a complex query you wrote involving multiple joins and subqueries. What was the business problem you were solving?
- Follow-Up: How did you ensure that the query performed efficiently?
7. Stored Procedures and Functions
- Question: Have you created stored procedures or functions in any of your projects? Can you describe one and explain why you chose to encapsulate the logic in a stored procedure?
- Follow-Up: How did you handle error handling and logging within the stored procedure?
8. Data Integrity and Constraints
- Question: How did you enforce data integrity in your SQL projects? Can you give examples of constraints (e.g., primary keys, foreign keys, unique constraints) you implemented?
- Follow-Up: How did you handle situations where constraints needed to be temporarily disabled or modified?
9. Version Control and Collaboration
- Question: How did you manage database version control in your projects? What tools or practices did you use to ensure collaboration with other developers?
- Follow-Up: How did you handle conflicts or issues arising from multiple developers working on the same database?
10. Data Migration
- Question: Describe a data migration project you worked on. How did you ensure that the migration was successful, and what steps did you take to handle data inconsistencies or errors?
- Follow-Up: How did you test the migration process before moving to the production environment?
11. Security and Permissions
- Question: In your SQL projects, how did you manage database security?
- Follow-Up: How did you handle encryption or sensitive data within the database?
12. Handling Unstructured Data
- Question: Have you worked with unstructured or semi-structured data in an SQL environment?
- Follow-Up: What challenges did you face, and how did you overcome them?
13. Real-Time Data Processing
- Question: Can you describe a project where you handled real-time data processing using SQL? What were the key challenges, and how did you address them?
- Follow-Up: How did you ensure the performance and reliability of the real-time data processing system?
Be prepared to discuss specific examples from your past work and explain your thought process in detail.
Here you can find SQL Interview Resources👇
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
❤2
DSA INTERVIEW QUESTIONS AND ANSWERS
1. What is the difference between file structure and storage structure?
The difference lies in the memory area accessed. Storage structure refers to the data structure in the memory of the computer system,
whereas file structure represents the storage structure in the auxiliary memory.
2. Are linked lists considered linear or non-linear Data Structures?
Linked lists are considered both linear and non-linear data structures depending upon the application they are used for. When used for
access strategies, it is considered as a linear data-structure. When used for data storage, it is considered a non-linear data structure.
3. How do you reference all of the elements in a one-dimension array?
All of the elements in a one-dimension array can be referenced using an indexed loop as the array subscript so that the counter runs
from 0 to the array size minus one.
4. What are dynamic Data Structures? Name a few.
They are collections of data in memory that expand and contract to grow or shrink in size as a program runs. This enables the programmer
to control exactly how much memory is to be utilized.Examples are the dynamic array, linked list, stack, queue, and heap.
5. What is a Dequeue?
It is a double-ended queue, or a data structure, where the elements can be inserted or deleted at both ends (FRONT and REAR).
6. What operations can be performed on queues?
enqueue() adds an element to the end of the queue
dequeue() removes an element from the front of the queue
init() is used for initializing the queue
isEmpty tests for whether or not the queue is empty
The front is used to get the value of the first data item but does not remove it
The rear is used to get the last item from a queue.
7. What is the merge sort? How does it work?
Merge sort is a divide-and-conquer algorithm for sorting the data. It works by merging and sorting adjacent data to create bigger sorted
lists, which are then merged recursively to form even bigger sorted lists until you have one single sorted list.
8.How does the Selection sort work?
Selection sort works by repeatedly picking the smallest number in ascending order from the list and placing it at the beginning. This process is repeated moving toward the end of the list or sorted subarray.
Scan all items and find the smallest. Switch over the position as the first item. Repeat the selection sort on the remaining N-1 items. We always iterate forward (i from 0 to N-1) and swap with the smallest element (always i).
Time complexity: best case O(n2); worst O(n2)
Space complexity: worst O(1)
9. What are the applications of graph Data Structure?
Transport grids where stations are represented as vertices and routes as the edges of the graph
Utility graphs of power or water, where vertices are connection points and edge the wires or pipes connecting them
Social network graphs to determine the flow of information and hotspots (edges and vertices)
Neural networks where vertices represent neurons and edge the synapses between them
10. What is an AVL tree?
An AVL (Adelson, Velskii, and Landi) tree is a height balancing binary search tree in which the difference of heights of the left
and right subtrees of any node is less than or equal to one. This controls the height of the binary search tree by not letting
it get skewed. This is used when working with a large data set, with continual pruning through insertion and deletion of data.
11. Differentiate NULL and VOID ?
Null is a value, whereas Void is a data type identifier
Null indicates an empty value for a variable, whereas void indicates pointers that have no initial size
Null means it never existed; Void means it existed but is not in effect
You can check these resources for Coding interview Preparation
Credits: https://t.iss.one/free4unow_backup
All the best 👍👍
1. What is the difference between file structure and storage structure?
The difference lies in the memory area accessed. Storage structure refers to the data structure in the memory of the computer system,
whereas file structure represents the storage structure in the auxiliary memory.
2. Are linked lists considered linear or non-linear Data Structures?
Linked lists are considered both linear and non-linear data structures depending upon the application they are used for. When used for
access strategies, it is considered as a linear data-structure. When used for data storage, it is considered a non-linear data structure.
3. How do you reference all of the elements in a one-dimension array?
All of the elements in a one-dimension array can be referenced using an indexed loop as the array subscript so that the counter runs
from 0 to the array size minus one.
4. What are dynamic Data Structures? Name a few.
They are collections of data in memory that expand and contract to grow or shrink in size as a program runs. This enables the programmer
to control exactly how much memory is to be utilized.Examples are the dynamic array, linked list, stack, queue, and heap.
5. What is a Dequeue?
It is a double-ended queue, or a data structure, where the elements can be inserted or deleted at both ends (FRONT and REAR).
6. What operations can be performed on queues?
enqueue() adds an element to the end of the queue
dequeue() removes an element from the front of the queue
init() is used for initializing the queue
isEmpty tests for whether or not the queue is empty
The front is used to get the value of the first data item but does not remove it
The rear is used to get the last item from a queue.
7. What is the merge sort? How does it work?
Merge sort is a divide-and-conquer algorithm for sorting the data. It works by merging and sorting adjacent data to create bigger sorted
lists, which are then merged recursively to form even bigger sorted lists until you have one single sorted list.
8.How does the Selection sort work?
Selection sort works by repeatedly picking the smallest number in ascending order from the list and placing it at the beginning. This process is repeated moving toward the end of the list or sorted subarray.
Scan all items and find the smallest. Switch over the position as the first item. Repeat the selection sort on the remaining N-1 items. We always iterate forward (i from 0 to N-1) and swap with the smallest element (always i).
Time complexity: best case O(n2); worst O(n2)
Space complexity: worst O(1)
9. What are the applications of graph Data Structure?
Transport grids where stations are represented as vertices and routes as the edges of the graph
Utility graphs of power or water, where vertices are connection points and edge the wires or pipes connecting them
Social network graphs to determine the flow of information and hotspots (edges and vertices)
Neural networks where vertices represent neurons and edge the synapses between them
10. What is an AVL tree?
An AVL (Adelson, Velskii, and Landi) tree is a height balancing binary search tree in which the difference of heights of the left
and right subtrees of any node is less than or equal to one. This controls the height of the binary search tree by not letting
it get skewed. This is used when working with a large data set, with continual pruning through insertion and deletion of data.
11. Differentiate NULL and VOID ?
Null is a value, whereas Void is a data type identifier
Null indicates an empty value for a variable, whereas void indicates pointers that have no initial size
Null means it never existed; Void means it existed but is not in effect
You can check these resources for Coding interview Preparation
Credits: https://t.iss.one/free4unow_backup
All the best 👍👍
❤1
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
DSA (Data Structures and Algorithms) Essential Topics for Interviews
1️⃣ Arrays and Strings
Basic operations (insert, delete, update)
Two-pointer technique
Sliding window
Prefix sum
Kadane’s algorithm
Subarray problems
2️⃣ Linked List
Singly & Doubly Linked List
Reverse a linked list
Detect loop (Floyd’s Cycle)
Merge two sorted lists
Intersection of linked lists
3️⃣ Stack & Queue
Stack using array or linked list
Queue and Circular Queue
Monotonic Stack/Queue
LRU Cache (LinkedHashMap/Deque)
Infix to Postfix conversion
4️⃣ Hashing
HashMap, HashSet
Frequency counting
Two Sum problem
Group Anagrams
Longest Consecutive Sequence
5️⃣ Recursion & Backtracking
Base cases and recursive calls
Subsets, permutations
N-Queens problem
Sudoku solver
Word search
6️⃣ Trees & Binary Trees
Traversals (Inorder, Preorder, Postorder)
Height and Diameter
Balanced Binary Tree
Lowest Common Ancestor (LCA)
Serialize & Deserialize Tree
7️⃣ Binary Search Trees (BST)
Search, Insert, Delete
Validate BST
Kth smallest/largest element
Convert BST to DLL
8️⃣ Heaps & Priority Queues
Min Heap / Max Heap
Heapify
Top K elements
Merge K sorted lists
Median in a stream
9️⃣ Graphs
Representations (adjacency list/matrix)
DFS, BFS
Cycle detection (directed & undirected)
Topological Sort
Dijkstra’s & Bellman-Ford algorithm
Union-Find (Disjoint Set)
10️⃣ Dynamic Programming (DP)
0/1 Knapsack
Longest Common Subsequence
Matrix Chain Multiplication
DP on subsequences
Memoization vs Tabulation
11️⃣ Greedy Algorithms
Activity selection
Huffman coding
Fractional knapsack
Job scheduling
12️⃣ Tries
Insert and search a word
Word search
Auto-complete feature
13️⃣ Bit Manipulation
XOR, AND, OR basics
Check if power of 2
Single Number problem
Count set bits
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
ENJOY LEARNING 👍👍
1️⃣ Arrays and Strings
Basic operations (insert, delete, update)
Two-pointer technique
Sliding window
Prefix sum
Kadane’s algorithm
Subarray problems
2️⃣ Linked List
Singly & Doubly Linked List
Reverse a linked list
Detect loop (Floyd’s Cycle)
Merge two sorted lists
Intersection of linked lists
3️⃣ Stack & Queue
Stack using array or linked list
Queue and Circular Queue
Monotonic Stack/Queue
LRU Cache (LinkedHashMap/Deque)
Infix to Postfix conversion
4️⃣ Hashing
HashMap, HashSet
Frequency counting
Two Sum problem
Group Anagrams
Longest Consecutive Sequence
5️⃣ Recursion & Backtracking
Base cases and recursive calls
Subsets, permutations
N-Queens problem
Sudoku solver
Word search
6️⃣ Trees & Binary Trees
Traversals (Inorder, Preorder, Postorder)
Height and Diameter
Balanced Binary Tree
Lowest Common Ancestor (LCA)
Serialize & Deserialize Tree
7️⃣ Binary Search Trees (BST)
Search, Insert, Delete
Validate BST
Kth smallest/largest element
Convert BST to DLL
8️⃣ Heaps & Priority Queues
Min Heap / Max Heap
Heapify
Top K elements
Merge K sorted lists
Median in a stream
9️⃣ Graphs
Representations (adjacency list/matrix)
DFS, BFS
Cycle detection (directed & undirected)
Topological Sort
Dijkstra’s & Bellman-Ford algorithm
Union-Find (Disjoint Set)
10️⃣ Dynamic Programming (DP)
0/1 Knapsack
Longest Common Subsequence
Matrix Chain Multiplication
DP on subsequences
Memoization vs Tabulation
11️⃣ Greedy Algorithms
Activity selection
Huffman coding
Fractional knapsack
Job scheduling
12️⃣ Tries
Insert and search a word
Word search
Auto-complete feature
13️⃣ Bit Manipulation
XOR, AND, OR basics
Check if power of 2
Single Number problem
Count set bits
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
ENJOY LEARNING 👍👍
❤4
🚀 Front-End Development Interview Topics
HTML & CSS
🔹 Semantic HTML
🔹 CSS Pre-Processors
🔹 CSS Specificity
🔹 Resetting & Normalizing CSS
🔹 CSS Architecture
🔹 SVGs
🔹 Media Queries
🔹 CSS Display Property
🔹 CSS Position Property
🔹 CSS Frameworks
🔹 Pseudo Classes
🔹 Sprites
JavaScript
🔹 Event Delegation
🔹 Attributes vs Properties
🔹 Ternary Operators
🔹 Promises vs Callbacks
🔹 Single Page Application
🔹 Higher-Order Functions
🔹 == vs ===
🔹 Mutable vs Immutable
🔹 'this'
🔹 Prototypal Inheritance
🔹 IFE (Immediately Invoked Function Expression)
🔹 Closure
🔹 Null vs Undefined
🔹 OOP vs Map
🔹 .call & .apply
🔹 Hoisting
🔹 Objects
🔹 Scope
🔹 JS Frameworks
Data Structures and Algorithms
🔹 Linked Lists
🔹 Hash Tables
🔹 Stacks
🔹 Queues
🔹 Trees
🔹 Graphs
🔹 Arrays
🔹 Bubble Sort
🔹 Binary Search
🔹 Selection Sort
🔹 Quick Sort
🔹 Insertion Sort
Front-End Topics
🔹 Performance
🔹 Unit Testing
🔹 End-to-End Testing (E2E)
🔹 Web Accessibility
🔹 CORS
🔹 SEO
🔹 REST
🔹 APIs
🔹 HTTP/HTTPS
🔹 GitHub
🔹 Task Runners
🔹 Browser APIs
HTML & CSS
🔹 Semantic HTML
🔹 CSS Pre-Processors
🔹 CSS Specificity
🔹 Resetting & Normalizing CSS
🔹 CSS Architecture
🔹 SVGs
🔹 Media Queries
🔹 CSS Display Property
🔹 CSS Position Property
🔹 CSS Frameworks
🔹 Pseudo Classes
🔹 Sprites
JavaScript
🔹 Event Delegation
🔹 Attributes vs Properties
🔹 Ternary Operators
🔹 Promises vs Callbacks
🔹 Single Page Application
🔹 Higher-Order Functions
🔹 == vs ===
🔹 Mutable vs Immutable
🔹 'this'
🔹 Prototypal Inheritance
🔹 IFE (Immediately Invoked Function Expression)
🔹 Closure
🔹 Null vs Undefined
🔹 OOP vs Map
🔹 .call & .apply
🔹 Hoisting
🔹 Objects
🔹 Scope
🔹 JS Frameworks
Data Structures and Algorithms
🔹 Linked Lists
🔹 Hash Tables
🔹 Stacks
🔹 Queues
🔹 Trees
🔹 Graphs
🔹 Arrays
🔹 Bubble Sort
🔹 Binary Search
🔹 Selection Sort
🔹 Quick Sort
🔹 Insertion Sort
Front-End Topics
🔹 Performance
🔹 Unit Testing
🔹 End-to-End Testing (E2E)
🔹 Web Accessibility
🔹 CORS
🔹 SEO
🔹 REST
🔹 APIs
🔹 HTTP/HTTPS
🔹 GitHub
🔹 Task Runners
🔹 Browser APIs
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