Git & Github interviews Q & A.pdf
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๐ GIT & GITHUB INTERVIEWS (Questions and Answers)
XML_JSON_Programming,_For_Beginners,_Learn_Coding.epub
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๐ XML JSON Programming For Beginners
git-cheat-sheet-education.pdf
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๐ GIT Cheatsheet Education
Coding Interview Preparation.pdf
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๐ Coding interview Preparation
keyboard-shortcuts-windows.pdf
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๐ Shortcuts for WINDOWS KEYBOARD
top-50-html-interview-questions.pdf
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Top 50 HTML INTERVIEW QUESTIONS ๐ฅ๐ฅ๐ฅ
Machine Learning Interview Questions.pdf.pdf
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๐ MACHINE LEARNING INTERVIEW QUESTIONS
Data Analyst Interview Questions.pdf
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๐ DATA ANALYST INTERVIEW QUESTIONS
Here are 10 popular programming languages based on versatile, widely-used, and in-demand languages:
1. Python โ Ideal for beginners and professionals; used in web development, data analysis, AI, and more.
2. Java โ A classic language for building enterprise applications, Android apps, and large-scale systems.
3. C โ The foundation for many other languages; great for understanding low-level programming concepts.
4. C++ โ Popular for game development, competitive programming, and performance-critical applications.
5. C# โ Widely used for Windows applications, game development (Unity), and enterprise software.
6. Go (Golang) โ A modern language designed for performance and scalability, popular in cloud services.
7. Rust โ Known for its safety and performance, ideal for system-level programming.
8. Kotlin โ The preferred language for Android development with modern features.
9. Swift โ Used for developing iOS and macOS applications with simplicity and power.
10. PHP โ A staple for web development, powering many websites and applications
1. Python โ Ideal for beginners and professionals; used in web development, data analysis, AI, and more.
2. Java โ A classic language for building enterprise applications, Android apps, and large-scale systems.
3. C โ The foundation for many other languages; great for understanding low-level programming concepts.
4. C++ โ Popular for game development, competitive programming, and performance-critical applications.
5. C# โ Widely used for Windows applications, game development (Unity), and enterprise software.
6. Go (Golang) โ A modern language designed for performance and scalability, popular in cloud services.
7. Rust โ Known for its safety and performance, ideal for system-level programming.
8. Kotlin โ The preferred language for Android development with modern features.
9. Swift โ Used for developing iOS and macOS applications with simplicity and power.
10. PHP โ A staple for web development, powering many websites and applications
๐ฐ Deep Python Roadmap for Beginners ๐
Setup & Installation ๐ฅ๏ธโ๏ธ
โข Install Python, choose an IDE (VS Code, PyCharm)
โข Set up virtual environments for project isolation ๐
Basic Syntax & Data Types ๐๐ข
โข Learn variables, numbers, strings, booleans
โข Understand comments, basic input/output, and simple expressions โ๏ธ
Control Flow & Loops ๐๐
โข Master conditionals (if, elif, else)
โข Practice loops (for, while) and use control statements like break and continue ๐ฎ
Functions & Scope โ๏ธ๐ฏ
โข Define functions with def and learn about parameters and return values
โข Explore lambda functions, recursion, and variable scope ๐
Data Structures ๐๐
โข Work with lists, tuples, sets, and dictionaries
โข Learn list comprehensions and built-in methods for data manipulation โ๏ธ
Object-Oriented Programming (OOP) ๐๏ธ๐ฉโ๐ป
โข Understand classes, objects, and methods
โข Dive into inheritance, polymorphism, and encapsulation ๐
React "โค๏ธ" for Part 2
Setup & Installation ๐ฅ๏ธโ๏ธ
โข Install Python, choose an IDE (VS Code, PyCharm)
โข Set up virtual environments for project isolation ๐
Basic Syntax & Data Types ๐๐ข
โข Learn variables, numbers, strings, booleans
โข Understand comments, basic input/output, and simple expressions โ๏ธ
Control Flow & Loops ๐๐
โข Master conditionals (if, elif, else)
โข Practice loops (for, while) and use control statements like break and continue ๐ฎ
Functions & Scope โ๏ธ๐ฏ
โข Define functions with def and learn about parameters and return values
โข Explore lambda functions, recursion, and variable scope ๐
Data Structures ๐๐
โข Work with lists, tuples, sets, and dictionaries
โข Learn list comprehensions and built-in methods for data manipulation โ๏ธ
Object-Oriented Programming (OOP) ๐๏ธ๐ฉโ๐ป
โข Understand classes, objects, and methods
โข Dive into inheritance, polymorphism, and encapsulation ๐
React "โค๏ธ" for Part 2
Part 2 of the Deep Python Roadmap for Beginners ๐ฐ
File Handling & Exceptions ๐๐จ
โข Read/write files (text, CSV, JSON)
โข Use try/except/finally for error handling
Modules & Environments ๐ฆ๐
โข Organize code with modules and packages
โข Manage dependencies with pip and virtual environments
Advanced Concepts ๐ฅ๐
โข Work with decorators, generators, and context managers
Testing & Debugging ๐โ
โข Write tests using unittest or pytest
โข Utilize debugging tools and linters
APIs & Web Development ๐๐
โข Interact with RESTful APIs
โข Start with frameworks like Flask or Django
Data Analysis & Visualization ๐๐จ
โข Use NumPy and Pandas for data handling
โข Visualize with Matplotlib or Seaborn
Asynchronous Programming โฐ๐
โข Learn threading, multiprocessing, and async/await
Version Control & Deployment ๐๐
โข Master Git basics and collaborative workflows
โข Explore deployment strategies and CI/CD practices
Project Building & Community ๐๏ธ๐
โข Build projects, contribute to open-source, and join communities
React โค๏ธ for more roadmaps
File Handling & Exceptions ๐๐จ
โข Read/write files (text, CSV, JSON)
โข Use try/except/finally for error handling
Modules & Environments ๐ฆ๐
โข Organize code with modules and packages
โข Manage dependencies with pip and virtual environments
Advanced Concepts ๐ฅ๐
โข Work with decorators, generators, and context managers
Testing & Debugging ๐โ
โข Write tests using unittest or pytest
โข Utilize debugging tools and linters
APIs & Web Development ๐๐
โข Interact with RESTful APIs
โข Start with frameworks like Flask or Django
Data Analysis & Visualization ๐๐จ
โข Use NumPy and Pandas for data handling
โข Visualize with Matplotlib or Seaborn
Asynchronous Programming โฐ๐
โข Learn threading, multiprocessing, and async/await
Version Control & Deployment ๐๐
โข Master Git basics and collaborative workflows
โข Explore deployment strategies and CI/CD practices
Project Building & Community ๐๏ธ๐
โข Build projects, contribute to open-source, and join communities
React โค๏ธ for more roadmaps
Theoretical Questions for Interviews on Array
1. What is an array?
An array is a data structure consisting of a collection of elements, each identified by at least one array index or key.
2. How do you declare an Array?
Each language has its own way of declaring arrays, but the general idea is similar: defining the type of elements and the number of elements or initializing it directly.
โ C/C++: int arr[5]; (Declares an array of 5 integers).
โ Java: int[] arr = new int[5]; (Declares and initializes an array of 5 integers).
โ Python: arr = [1, 2, 3, 4, 5] (Uses a list, which functions like an array and doesnโt require a fixed size).
โ JavaScript: let arr = [1, 2, 3, 4, 5]; (Uses arrays without needing a size specification).
โ C#: int[] arr = new int[5]; (Declares an array of 5 integers).
3. Can an array be resized at runtime?
An array is fixed in size once created. However, in C, you can resize an array at runtime using Dynamic Memory Allocation (DMA) with malloc() or realloc(). Most modern languages have dynamic-sized arrays like vector in C++, list in Python, and ArrayList in Java, which automatically resize.
4. Is it possible to declare an array without specifying its size?
In C/C++, declaring an array without specifying its size is not allowed and causes a compile-time error. However, in C, we can create a pointer and allocate memory dynamically using malloc(). In C++, we can use vectors where we can declare first and then dynamically add elements. In modern languages like Java, Python, and JavaScript, we can declare without specifying the size.
5. What is the time complexity for accessing an element in an array?
The time complexity for accessing an element in an array is O(1), as it can be accessed directly using its index.
6. What is the difference between an array and a linked list?
An array is a static data structure, while a linked list is a dynamic data structure. Raw arrays have a fixed size, and elements are stored consecutively in memory, while linked lists can grow dynamically and do not require contiguous memory allocation. Dynamic-sized arrays allow flexible size, but the worst-case time complexity for insertion/deletion at the end becomes more than O(1). With a linked list, we get O(1) worst-case time complexity for insertion and deletion.
7. How would you find out the smallest and largest element in an array?
The best approach is iterative (linear search), while other approaches include recursive and sorting.
Iterative method
Algorithm:
1. Initialize two variables:
small = arr[0] (first element as the smallest).
large = arr[0] (first element as the largest).
2. Traverse through the array from index 1 to n-1.
3. If arr[i] > large, update large = arr[i].
4. If arr[i] < small, update small = arr[i].
5. Print the values of small and large.
C++ Code Implementation
#include <iostream>
using namespace std;
void findMinMax(int arr[], int n) {
int small = arr[0], large = arr[0];
for (int i = 1; i < n; i++) {
if (arr[i] > large)
large = arr[i];
if (arr[i] < small)
small = arr[i];
}
cout << "Smallest element: " << small << endl;
cout << "Largest element: " << large << endl;
}
int main() {
int arr[] = {7, 2, 9, 4, 1, 5};
int n = sizeof(arr) / sizeof(arr[0]);
findMinMax(arr, n);
return 0;
}
8. What is the time complexity to search in an unsorted and sorted array?
โ Unsorted Array: The time complexity for searching an element in an unsorted array is O(n), as we may need to check every element.
โ Sorted Array: The time complexity for searching an element in a sorted array is O(log n) using binary search.
๐น O(log n) takes less time than O(n), whereas O(n log n) takes more time than O(n).
1. What is an array?
An array is a data structure consisting of a collection of elements, each identified by at least one array index or key.
2. How do you declare an Array?
Each language has its own way of declaring arrays, but the general idea is similar: defining the type of elements and the number of elements or initializing it directly.
โ C/C++: int arr[5]; (Declares an array of 5 integers).
โ Java: int[] arr = new int[5]; (Declares and initializes an array of 5 integers).
โ Python: arr = [1, 2, 3, 4, 5] (Uses a list, which functions like an array and doesnโt require a fixed size).
โ JavaScript: let arr = [1, 2, 3, 4, 5]; (Uses arrays without needing a size specification).
โ C#: int[] arr = new int[5]; (Declares an array of 5 integers).
3. Can an array be resized at runtime?
An array is fixed in size once created. However, in C, you can resize an array at runtime using Dynamic Memory Allocation (DMA) with malloc() or realloc(). Most modern languages have dynamic-sized arrays like vector in C++, list in Python, and ArrayList in Java, which automatically resize.
4. Is it possible to declare an array without specifying its size?
In C/C++, declaring an array without specifying its size is not allowed and causes a compile-time error. However, in C, we can create a pointer and allocate memory dynamically using malloc(). In C++, we can use vectors where we can declare first and then dynamically add elements. In modern languages like Java, Python, and JavaScript, we can declare without specifying the size.
5. What is the time complexity for accessing an element in an array?
The time complexity for accessing an element in an array is O(1), as it can be accessed directly using its index.
6. What is the difference between an array and a linked list?
An array is a static data structure, while a linked list is a dynamic data structure. Raw arrays have a fixed size, and elements are stored consecutively in memory, while linked lists can grow dynamically and do not require contiguous memory allocation. Dynamic-sized arrays allow flexible size, but the worst-case time complexity for insertion/deletion at the end becomes more than O(1). With a linked list, we get O(1) worst-case time complexity for insertion and deletion.
7. How would you find out the smallest and largest element in an array?
The best approach is iterative (linear search), while other approaches include recursive and sorting.
Iterative method
Algorithm:
1. Initialize two variables:
small = arr[0] (first element as the smallest).
large = arr[0] (first element as the largest).
2. Traverse through the array from index 1 to n-1.
3. If arr[i] > large, update large = arr[i].
4. If arr[i] < small, update small = arr[i].
5. Print the values of small and large.
C++ Code Implementation
#include <iostream>
using namespace std;
void findMinMax(int arr[], int n) {
int small = arr[0], large = arr[0];
for (int i = 1; i < n; i++) {
if (arr[i] > large)
large = arr[i];
if (arr[i] < small)
small = arr[i];
}
cout << "Smallest element: " << small << endl;
cout << "Largest element: " << large << endl;
}
int main() {
int arr[] = {7, 2, 9, 4, 1, 5};
int n = sizeof(arr) / sizeof(arr[0]);
findMinMax(arr, n);
return 0;
}
8. What is the time complexity to search in an unsorted and sorted array?
โ Unsorted Array: The time complexity for searching an element in an unsorted array is O(n), as we may need to check every element.
โ Sorted Array: The time complexity for searching an element in a sorted array is O(log n) using binary search.
๐น O(log n) takes less time than O(n), whereas O(n log n) takes more time than O(n).