7. Web Programming:
Learn how to build your website.
https://pll.harvard.edu/course/cs50s-web-programming-python-and-javascript
Share this telegram channel with your friends: https://t.iss.one/udacityfreecourse
Learn how to build your website.
https://pll.harvard.edu/course/cs50s-web-programming-python-and-javascript
Share this telegram channel with your friends: https://t.iss.one/udacityfreecourse
Three different learning styles in machine learning algorithms:
1. Supervised Learning
Input data is called training data and has a known label or result such as spam/not-spam or a stock price at a time.
A model is prepared through a training process in which it is required to make predictions and is corrected when those predictions are wrong. The training process continues until the model achieves a desired level of accuracy on the training data.
Example problems are classification and regression.
Example algorithms include: Logistic Regression and the Back Propagation Neural Network.
2. Unsupervised Learning
Input data is not labeled and does not have a known result.
A model is prepared by deducing structures present in the input data. This may be to extract general rules. It may be through a mathematical process to systematically reduce redundancy, or it may be to organize data by similarity.
Example problems are clustering, dimensionality reduction and association rule learning.
Example algorithms include: the Apriori algorithm and K-Means.
3. Semi-Supervised Learning
Input data is a mixture of labeled and unlabelled examples.
There is a desired prediction problem but the model must learn the structures to organize the data as well as make predictions.
Example problems are classification and regression.
Example algorithms are extensions to other flexible methods that make assumptions about how to model the unlabeled data.
1. Supervised Learning
Input data is called training data and has a known label or result such as spam/not-spam or a stock price at a time.
A model is prepared through a training process in which it is required to make predictions and is corrected when those predictions are wrong. The training process continues until the model achieves a desired level of accuracy on the training data.
Example problems are classification and regression.
Example algorithms include: Logistic Regression and the Back Propagation Neural Network.
2. Unsupervised Learning
Input data is not labeled and does not have a known result.
A model is prepared by deducing structures present in the input data. This may be to extract general rules. It may be through a mathematical process to systematically reduce redundancy, or it may be to organize data by similarity.
Example problems are clustering, dimensionality reduction and association rule learning.
Example algorithms include: the Apriori algorithm and K-Means.
3. Semi-Supervised Learning
Input data is a mixture of labeled and unlabelled examples.
There is a desired prediction problem but the model must learn the structures to organize the data as well as make predictions.
Example problems are classification and regression.
Example algorithms are extensions to other flexible methods that make assumptions about how to model the unlabeled data.
👍2
🚀 Fun Facts About Data Science 🚀
1️⃣ Data Science is Everywhere - From Netflix recommendations to fraud detection in banking, data science powers everyday decisions.
2️⃣ 80% of a Data Scientist's Job is Data Cleaning - The real magic happens before the analysis. Messy data = messy results!
3️⃣ Python is the Most Popular Language - Loved for its simplicity and versatility, Python is the go-to for data analysis, machine learning, and automation.
4️⃣ Data Visualization Tells a Story - A well-designed chart or dashboard can reveal insights faster than thousands of rows in a spreadsheet.
5️⃣ AI is Making Data Science More Powerful - Machine learning models are now helping businesses predict trends, automate processes, and improve decision-making.
Stay curious and keep exploring the fascinating world of data science! 🌐📊
#DataScience #Python #AI #MachineLearning #DataVisualization
1️⃣ Data Science is Everywhere - From Netflix recommendations to fraud detection in banking, data science powers everyday decisions.
2️⃣ 80% of a Data Scientist's Job is Data Cleaning - The real magic happens before the analysis. Messy data = messy results!
3️⃣ Python is the Most Popular Language - Loved for its simplicity and versatility, Python is the go-to for data analysis, machine learning, and automation.
4️⃣ Data Visualization Tells a Story - A well-designed chart or dashboard can reveal insights faster than thousands of rows in a spreadsheet.
5️⃣ AI is Making Data Science More Powerful - Machine learning models are now helping businesses predict trends, automate processes, and improve decision-making.
Stay curious and keep exploring the fascinating world of data science! 🌐📊
#DataScience #Python #AI #MachineLearning #DataVisualization
👍1
Sample email template to reach out to HR’s as fresher
I hope you will found this helpful 🙂
Hi Jasneet,
I recently came across your LinkedIn post seeking a React.js developer intern, and I am writing to express my interest in the position at Airtel. As a recent graduate, I am eager to begin my career and am excited about the opportunity.
I am a quick learner and have developed a strong set of dynamic and user-friendly web applications using various technologies, including HTML, CSS, JavaScript, Bootstrap, React.js, Vue.js, PHP, and MySQL. I am also well-versed in creating reusable components, implementing responsive designs, and ensuring cross-browser compatibility.
I am confident that my eagerness to learn and strong work ethic will make me an asset to your team.
I have attached my resume for your review. Thank you for considering my application. I look forward to hearing from you soon.
Thanks!I hope you will found this helpful 🙂
👍2❤1
Build Your First AI Agent (Live Session)
GeeksforGeeks is teaming up with Salesforce for a hands-on workshop on AI Agents for working professionals
You'll learn how to:
- Use the Agent Builder
- Customize AI agents for real business tasks
- Assign actions to your agents
No fluff. Just a practical session to get started with AI agents inside Salesforce.
You’ll also get a Free Certificate of Participation
Registration link:👇
https://gfgcdn.com/tu/V4t/
GeeksforGeeks is teaming up with Salesforce for a hands-on workshop on AI Agents for working professionals
You'll learn how to:
- Use the Agent Builder
- Customize AI agents for real business tasks
- Assign actions to your agents
No fluff. Just a practical session to get started with AI agents inside Salesforce.
You’ll also get a Free Certificate of Participation
Registration link:👇
https://gfgcdn.com/tu/V4t/
❤2👍2
React.js 30 Days Roadmap & Free Learning Resource 📍👇
👨🏻💻Days 1-7: Introduction and Fundamentals
📍Day 1: Introduction to React.js
What is React.js?
Setting up a development environment
Creating a basic React app
📍Day 2: JSX and Components
Understanding JSX
Creating functional components
Using props to pass data
📍Day 3: State and Lifecycle
Component state
Lifecycle methods (componentDidMount, componentDidUpdate, etc.)
Updating and rendering based on state changes
📍Day 4: Handling Events
Adding event handlers
Updating state with events
Conditional rendering
📍Day 5: Lists and Keys
Rendering lists of components
Adding unique keys to components
Handling list updates efficiently
📍Day 6: Forms and Controlled Components
Creating forms in React
Handling form input and validation
Controlled components
📍Day 7: Conditional Rendering
Conditional rendering with if statements
Using the && operator and ternary operator
Conditional rendering with logical AND (&&) and logical OR (||)
👨🏻💻Days 8-14: Advanced React Concepts
📍Day 8: Styling in React
Inline styles in React
Using CSS classes and libraries
CSS-in-JS solutions
📍Day 9: React Router
Setting up React Router
Navigating between routes
Passing data through routes
📍Day 10: Context API and State Management
Introduction to the Context API
Creating and consuming context
Global state management with context
📍Day 11: Redux for State Management
What is Redux?
Actions, reducers, and the store
Integrating Redux into a React application
📍Day 12: React Hooks (useState, useEffect, etc.)
Introduction to React Hooks
useState, useEffect, and other commonly used hooks
Refactoring class components to functional components with hooks
📍Day 13: Error Handling and Debugging
Error boundaries
Debugging React applications
Error handling best practices
📍Day 14: Building and Optimizing for Production
Production builds and optimizations
Code splitting
Performance best practices
👨🏻💻Days 15-21: Working with External Data and APIs
📍Day 15: Fetching Data from an API
Making API requests in React
Handling API responses
Async/await in React
📍Day 16: Forms and Form Libraries
Working with form libraries like Formik or React Hook Form
Form validation and error handling
📍Day 17: Authentication and User Sessions
Implementing user authentication
Handling user sessions and tokens
Securing routes
📍Day 18: State Management with Redux Toolkit
Introduction to Redux Toolkit
Creating slices
Simplified Redux configuration
📍Day 19: Routing in Depth
Nested routing with React Router
Route guards and authentication
Advanced route configuration
📍Day 20: Performance Optimization
Memoization and useMemo
React.iss.onemo for optimizing components
Virtualization and large lists
📍Day 21: Real-time Data with WebSockets
WebSockets for real-time communication
Implementing chat or notifications
👨🏻💻Days 22-30: Building and Deployment
📍Day 22: Building a Full-Stack App
Integrating React with a backend (e.g., Node.js, Express, or a serverless platform)
Implementing RESTful or GraphQL APIs
📍Day 23: Testing in React
Testing React components using tools like Jest and React Testing Library
Writing unit tests and integration tests
📍Day 24: Deployment and Hosting
Preparing your React app for production
Deploying to platforms like Netlify, Vercel, or AWS
📍Day 25-30: Final Project
*_Plan, design, and build a complete React project of your choice, incorporating various concepts and tools you've learned during the previous days.
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING 👍👍
👨🏻💻Days 1-7: Introduction and Fundamentals
📍Day 1: Introduction to React.js
What is React.js?
Setting up a development environment
Creating a basic React app
📍Day 2: JSX and Components
Understanding JSX
Creating functional components
Using props to pass data
📍Day 3: State and Lifecycle
Component state
Lifecycle methods (componentDidMount, componentDidUpdate, etc.)
Updating and rendering based on state changes
📍Day 4: Handling Events
Adding event handlers
Updating state with events
Conditional rendering
📍Day 5: Lists and Keys
Rendering lists of components
Adding unique keys to components
Handling list updates efficiently
📍Day 6: Forms and Controlled Components
Creating forms in React
Handling form input and validation
Controlled components
📍Day 7: Conditional Rendering
Conditional rendering with if statements
Using the && operator and ternary operator
Conditional rendering with logical AND (&&) and logical OR (||)
👨🏻💻Days 8-14: Advanced React Concepts
📍Day 8: Styling in React
Inline styles in React
Using CSS classes and libraries
CSS-in-JS solutions
📍Day 9: React Router
Setting up React Router
Navigating between routes
Passing data through routes
📍Day 10: Context API and State Management
Introduction to the Context API
Creating and consuming context
Global state management with context
📍Day 11: Redux for State Management
What is Redux?
Actions, reducers, and the store
Integrating Redux into a React application
📍Day 12: React Hooks (useState, useEffect, etc.)
Introduction to React Hooks
useState, useEffect, and other commonly used hooks
Refactoring class components to functional components with hooks
📍Day 13: Error Handling and Debugging
Error boundaries
Debugging React applications
Error handling best practices
📍Day 14: Building and Optimizing for Production
Production builds and optimizations
Code splitting
Performance best practices
👨🏻💻Days 15-21: Working with External Data and APIs
📍Day 15: Fetching Data from an API
Making API requests in React
Handling API responses
Async/await in React
📍Day 16: Forms and Form Libraries
Working with form libraries like Formik or React Hook Form
Form validation and error handling
📍Day 17: Authentication and User Sessions
Implementing user authentication
Handling user sessions and tokens
Securing routes
📍Day 18: State Management with Redux Toolkit
Introduction to Redux Toolkit
Creating slices
Simplified Redux configuration
📍Day 19: Routing in Depth
Nested routing with React Router
Route guards and authentication
Advanced route configuration
📍Day 20: Performance Optimization
Memoization and useMemo
React.iss.onemo for optimizing components
Virtualization and large lists
📍Day 21: Real-time Data with WebSockets
WebSockets for real-time communication
Implementing chat or notifications
👨🏻💻Days 22-30: Building and Deployment
📍Day 22: Building a Full-Stack App
Integrating React with a backend (e.g., Node.js, Express, or a serverless platform)
Implementing RESTful or GraphQL APIs
📍Day 23: Testing in React
Testing React components using tools like Jest and React Testing Library
Writing unit tests and integration tests
📍Day 24: Deployment and Hosting
Preparing your React app for production
Deploying to platforms like Netlify, Vercel, or AWS
📍Day 25-30: Final Project
*_Plan, design, and build a complete React project of your choice, incorporating various concepts and tools you've learned during the previous days.
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING 👍👍
👍2
Useful VSCode Shortcuts List📝👨🏻💻
Ctrl + A - Select All
Alt + Shift + Up/Down - Copy Line Up/Down
Ctrl + Shift + K - Delete Line
Alt + Up/Down - Move Line Up/Down
Ctrl +
Ctrl + Shift + L - Select All Occurrences
Ctrl + D - Add Selection to Next Find Match
Ctrl + Shift + D - Start/Stop Debugging
Ctrl + Shift + C - Open External Terminal
Ctrl + Shift + V - Open Markdown Preview
Ctrl + Shift + I - Format Document
Ctrl + Shift + U - Show Output
Ctrl + Shift + P - Open Command Palette
Ctrl + Shift + J - Open Debug Console
Ctrl + Shift + F12 - Toggle Full Screen
Ctrl + Shift + E - Toggle Explorer
Ctrl + Shift + T - Reopen Closed File
Ctrl + / - Toggle Line Comment
Ctrl + Shift + / - Toggle Block Comment
Alt + Shift + F - Format Document
Ctrl + K, Ctrl + S - Show Keyboard Shortcuts
#coding
Ctrl + A - Select All
Alt + Shift + Up/Down - Copy Line Up/Down
Ctrl + Shift + K - Delete Line
Alt + Up/Down - Move Line Up/Down
Ctrl +
- Toggle Terminal
Ctrl + B - Toggle Sidebar
Ctrl + Shift + D - Toggle Debug Panel
F5 - Start Debugging
Ctrl + Shift + E - Open Explorer
Ctrl + Shift + F - Find in Files
Ctrl + Shift + H - Replace in Files
Ctrl + Shift + M - Open Problems Panel
Ctrl + Shift + X - Open Extensions
Ctrl + Shift + - Show Integrated TerminalCtrl + Shift + L - Select All Occurrences
Ctrl + D - Add Selection to Next Find Match
Ctrl + Shift + D - Start/Stop Debugging
Ctrl + Shift + C - Open External Terminal
Ctrl + Shift + V - Open Markdown Preview
Ctrl + Shift + I - Format Document
Ctrl + Shift + U - Show Output
Ctrl + Shift + P - Open Command Palette
Ctrl + Shift + J - Open Debug Console
Ctrl + Shift + F12 - Toggle Full Screen
Ctrl + Shift + E - Toggle Explorer
Ctrl + Shift + T - Reopen Closed File
Ctrl + / - Toggle Line Comment
Ctrl + Shift + / - Toggle Block Comment
Alt + Shift + F - Format Document
Ctrl + K, Ctrl + S - Show Keyboard Shortcuts
#coding
👍4
Java coding interview questions
1. Reverse a String:
Write a Java program to reverse a given string.
2. Find the Largest Element in an Array:
Find and print the largest element in an array.
3. Check for Palindrome:
Determine if a given string is a palindrome (reads the same backward as forward).
4. Factorial Calculation:
Write a function to calculate the factorial of a number.
5. Fibonacci Series:
Generate the first n numbers in the Fibonacci sequence.
6. Check for Prime Number:
Write a program to check if a given number is prime.
7. String Anagrams:
Determine if two strings are anagrams of each other.
8. Array Sorting:
Implement sorting algorithms like bubble sort, merge sort, or quicksort.
9. Binary Search:
Implement a binary search algorithm to find an element in a sorted array.
10. Duplicate Elements in an Array:
Find and print duplicate elements in an array.
11. Linked List Reversal:
Reverse a singly-linked list.
12. Matrix Operations:
Perform matrix operations like addition, multiplication, or transpose.
13. Implement a Stack:
Create a stack data structure and implement basic operations (push, pop).
14. Implement a Queue:
Create a queue data structure and implement basic operations (enqueue, dequeue).
15. Inheritance and Polymorphism:
Implement a class hierarchy with inheritance and demonstrate polymorphism.
16. Exception Handling:
Write code that demonstrates the use of try-catch blocks to handle exceptions.
17. File I/O:
Read from and write to a file using Java's file I/O capabilities.
18. Multithreading:
Create a simple multithreaded program and demonstrate thread synchronization.
19. Lambda Expressions:
Use lambda expressions to implement functional interfaces.
20. Recursive Algorithms:
Solve a problem using recursion, such as computing the factorial or Fibonacci sequence.
Best Java Resources: https://t.iss.one/Java_Programming_Notes
Like for more ❤️
1. Reverse a String:
Write a Java program to reverse a given string.
2. Find the Largest Element in an Array:
Find and print the largest element in an array.
3. Check for Palindrome:
Determine if a given string is a palindrome (reads the same backward as forward).
4. Factorial Calculation:
Write a function to calculate the factorial of a number.
5. Fibonacci Series:
Generate the first n numbers in the Fibonacci sequence.
6. Check for Prime Number:
Write a program to check if a given number is prime.
7. String Anagrams:
Determine if two strings are anagrams of each other.
8. Array Sorting:
Implement sorting algorithms like bubble sort, merge sort, or quicksort.
9. Binary Search:
Implement a binary search algorithm to find an element in a sorted array.
10. Duplicate Elements in an Array:
Find and print duplicate elements in an array.
11. Linked List Reversal:
Reverse a singly-linked list.
12. Matrix Operations:
Perform matrix operations like addition, multiplication, or transpose.
13. Implement a Stack:
Create a stack data structure and implement basic operations (push, pop).
14. Implement a Queue:
Create a queue data structure and implement basic operations (enqueue, dequeue).
15. Inheritance and Polymorphism:
Implement a class hierarchy with inheritance and demonstrate polymorphism.
16. Exception Handling:
Write code that demonstrates the use of try-catch blocks to handle exceptions.
17. File I/O:
Read from and write to a file using Java's file I/O capabilities.
18. Multithreading:
Create a simple multithreaded program and demonstrate thread synchronization.
19. Lambda Expressions:
Use lambda expressions to implement functional interfaces.
20. Recursive Algorithms:
Solve a problem using recursion, such as computing the factorial or Fibonacci sequence.
Best Java Resources: https://t.iss.one/Java_Programming_Notes
Like for more ❤️
👍2
Programming languages and their uses in Ethical hacking :
Programming languages are essential tools for ethical hackers. They are used for tasks such as vulnerability testing, penetration testing, and developing exploits. Here are some programming languages that are commonly used in ethical hacking and their specific uses:
Python: Python is a high-level programming language that is easy to learn and widely used in the field of cybersecurity. It is used for tasks such as penetration testing, reverse engineering, and scripting. Python has a large community of developers who create and maintain libraries that can be used for security purposes, such as Scapy for packet manipulation, PyCrypto for encryption and decryption, and BeautifulSoup for web scraping.
Ruby: Ruby is another high-level programming language that is popular in the cybersecurity community. It is used for developing exploits and automating tasks. Metasploit, one of the most widely used penetration testing tools, is written in Ruby.
C/C++: C and C++ are low-level programming languages that are used for writing exploits and developing rootkits. They are also used for reverse engineering and vulnerability testing. Many of the tools used in ethical hacking, such as Nmap, Wireshark, and Tcpdump, are written in C/C++.
JavaScript: JavaScript is a popular scripting language that is used for web application security testing. It is used for tasks such as cross-site scripting (XSS) and cross-site request forgery (CSRF) testing. Many web-based security tools, such as Burp Suite, are written in JavaScript.
Bash: Bash is a shell scripting language that is used for automating tasks and creating custom scripts. It is commonly used for tasks such as password cracking and network scanning.
SQL: SQL is a database programming language that is used for exploiting and testing SQL injection vulnerabilities in web applications.
In addition to these languages, there are many other programming languages that can be used in ethical hacking, such as Perl, PHP, and Java. The choice of programming language will depend on the specific task at hand and the preference of the individual ethical hacker.
Programming languages are essential tools for ethical hackers. They are used for tasks such as vulnerability testing, penetration testing, and developing exploits. Here are some programming languages that are commonly used in ethical hacking and their specific uses:
Python: Python is a high-level programming language that is easy to learn and widely used in the field of cybersecurity. It is used for tasks such as penetration testing, reverse engineering, and scripting. Python has a large community of developers who create and maintain libraries that can be used for security purposes, such as Scapy for packet manipulation, PyCrypto for encryption and decryption, and BeautifulSoup for web scraping.
Ruby: Ruby is another high-level programming language that is popular in the cybersecurity community. It is used for developing exploits and automating tasks. Metasploit, one of the most widely used penetration testing tools, is written in Ruby.
C/C++: C and C++ are low-level programming languages that are used for writing exploits and developing rootkits. They are also used for reverse engineering and vulnerability testing. Many of the tools used in ethical hacking, such as Nmap, Wireshark, and Tcpdump, are written in C/C++.
JavaScript: JavaScript is a popular scripting language that is used for web application security testing. It is used for tasks such as cross-site scripting (XSS) and cross-site request forgery (CSRF) testing. Many web-based security tools, such as Burp Suite, are written in JavaScript.
Bash: Bash is a shell scripting language that is used for automating tasks and creating custom scripts. It is commonly used for tasks such as password cracking and network scanning.
SQL: SQL is a database programming language that is used for exploiting and testing SQL injection vulnerabilities in web applications.
In addition to these languages, there are many other programming languages that can be used in ethical hacking, such as Perl, PHP, and Java. The choice of programming language will depend on the specific task at hand and the preference of the individual ethical hacker.
❤2
Top Platforms for Building Data Science Portfolio
Build an irresistible portfolio that hooks recruiters with these free platforms.
Landing a job as a data scientist begins with building your portfolio with a comprehensive list of all your projects. To help you get started with building your portfolio, here is the list of top data science platforms. Remember the stronger your portfolio, the better chances you have of landing your dream job.
1. GitHub
2. Kaggle
3. LinkedIn
4. Medium
5. MachineHack
6. DagsHub
7. HuggingFace
7 Websites to Learn Data Science for FREE🧑💻
✅ w3school
✅ datasimplifier
✅ hackerrank
✅ kaggle
✅ geeksforgeeks
✅ leetcode
✅ freecodecamp
Build an irresistible portfolio that hooks recruiters with these free platforms.
Landing a job as a data scientist begins with building your portfolio with a comprehensive list of all your projects. To help you get started with building your portfolio, here is the list of top data science platforms. Remember the stronger your portfolio, the better chances you have of landing your dream job.
1. GitHub
2. Kaggle
3. LinkedIn
4. Medium
5. MachineHack
6. DagsHub
7. HuggingFace
7 Websites to Learn Data Science for FREE🧑💻
✅ w3school
✅ datasimplifier
✅ hackerrank
✅ kaggle
✅ geeksforgeeks
✅ leetcode
✅ freecodecamp
👍2
We have the Key to unlock AI-Powered Data Skills!
We have got some news for College grads & pros:
Level up with PW Skills' Data Analytics & Data Science with Gen AI course!
✅ Real-world projects
✅ Professional instructors
✅ Flexible learning
✅ Job Assistance
Ready for a data career boost? ➡️
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https://shorturl.at/7nrE5
We have got some news for College grads & pros:
Level up with PW Skills' Data Analytics & Data Science with Gen AI course!
✅ Real-world projects
✅ Professional instructors
✅ Flexible learning
✅ Job Assistance
Ready for a data career boost? ➡️
Click Here for Data Science with Generative AI Course:
https://shorturl.at/j4lTD
Click Here for Data Analytics Course:
https://shorturl.at/7nrE5
👍1
❇️ How to Find Server’s IP Address of Any Website
➖➖➖➖➖➖➖➖➖➖➖➖➖➖
💠 Using Command Prompt For Windows
👉 In this method essentially ping commands work for us to locate the IP address of any site. Actually, the ping command works on ICMP protocol which is made for servers address. Hence this command uses to locate the server address.
🔹Step 1: Click on the Start button and type CMD. Open CMD from the list.
🔹Step 2: Now you will see an elevated Command Prompt Window.
🔹Step 3: Type ping Site name (for ex-ping Kalilinux.com ).
And press Enter.
✅ Now, this will show you the IP address of the site and all trip details of the site location.
💠 Using Terminal In MAC Or Linux
👉 The terminal is like the command prompt but it is for Linux and macOS. In this, we can use the same command that we did in CMD. Now in this terminal, you will lookup for the Ip address of any site using a simple command.
🔹Step 1: Open terminal by a pressing CTRL+ALT+T ok keyboard at once.
🔹Step 2: Now type ping -c1 Sitename (for ex:- ping -c1 kalilinux.com).
✅ The above command will display the IP address of the entered website.
➖➖➖➖➖➖➖➖➖➖➖➖➖➖
💠 Using Command Prompt For Windows
👉 In this method essentially ping commands work for us to locate the IP address of any site. Actually, the ping command works on ICMP protocol which is made for servers address. Hence this command uses to locate the server address.
🔹Step 1: Click on the Start button and type CMD. Open CMD from the list.
🔹Step 2: Now you will see an elevated Command Prompt Window.
🔹Step 3: Type ping Site name (for ex-ping Kalilinux.com ).
And press Enter.
✅ Now, this will show you the IP address of the site and all trip details of the site location.
💠 Using Terminal In MAC Or Linux
👉 The terminal is like the command prompt but it is for Linux and macOS. In this, we can use the same command that we did in CMD. Now in this terminal, you will lookup for the Ip address of any site using a simple command.
🔹Step 1: Open terminal by a pressing CTRL+ALT+T ok keyboard at once.
🔹Step 2: Now type ping -c1 Sitename (for ex:- ping -c1 kalilinux.com).
✅ The above command will display the IP address of the entered website.
👍1