Here's the sample answer to "Tell me about yourself?" according to the most common job roles๐๐
Frontend Developer-
Backend Developer-
Full-Stack Developer -
I hope you will find this helpful ๐โค๏ธ
Frontend Developer-
Hi Iโm [Your Name] and I'm a passionate front-end developer with [X years] of experience building user-friendly web interfaces. I'm proficient in HTML, CSS, and JavaScript, and I have a strong understanding of frameworks like React. I prioritize crafting clean, responsive code that delivers a seamless user experience.Backend Developer-
Hi Iโm [Your Name] and I'm a skilled backend developer with a strong foundation in [mention your primary languages]. I possess expertise in server-side development, database management using SQL, and experience with frameworks like [mention relevant frameworks]. I enjoy tackling complex challenges and building robust, scalable back-end systems.Full-Stack Developer -
Hi Iโm [Your Name] and I'm a passionate full-stack developer with [X years] of experience building web applications. I'm proficient in both front-end technologies like HTML, CSS, and JavaScript frameworks like [mention relevant ones]. I also have a strong understanding of back-end development using [mention languages like Python, Java] and frameworks like [mention relevant ones]. I enjoy tackling complex challenges and delivering user-centric solutions throughout the development cycle.
I hope you will find this helpful ๐โค๏ธ
โค3๐2๐1
Commonly asked System Design CONCEPT BASED interview topics -
1. Horizontal vs Vertical Partitioning:
Vertical partitioning splits tables by columns, often separating different features. Horizontal partitioning splits tables by rows, distributing data across multiple servers. Vertical organizes data logically, while horizontal improves scalability + performance.
2. Apache Kafka:
Kafka is a distributed streaming platform using a publish-subscribe model. It's fast due to the sequential disk I/O, zero-copy principle, and efficient batching of messages.
3. Rate Limiter:
A rate limiter controls the rate of requests a client can make to a service. It prevents overload and ensures fair resource usage.
4. JWT vs OAuth vs SAML:
JWT is a compact, self-contained token for secure information transmission. OAuth is an authorization framework for delegated access. SAML is an XML-based standard for exchanging authentication and authorization data.
5. Single Sign-On (SSO):
SSO allows users to access multiple applications with one set of credentials. It typically uses a central authentication server and protocols like SAML/OAuth.
6. Microservices vs Monolithic Architecture:
Microservices architecture breaks an application into small, independent services. Monolithic architecture is a single, tightly-coupled unit. Microservices offer scalability while monoliths are simpler to develop + deploy.
7. Reverse Proxy vs Forward Proxy:
A reverse proxy sits in front of web servers, forwarding client requests to backend servers. A forward proxy sits in front of clients, forwarding their requests to the internet. Reverse proxies are used for load balancing and security, while forward proxies are used for anonymity and filtering.
8. CAP Theorem:
The CAP theorem states that a distributed system can only provide two of three guarantees: Consistency, Availability, and Partition tolerance. In practice, partition tolerance is necessary, so systems must choose between consistency and availability during network partitions.
10. Efficient Caching Strategy:
Implement multi-level caching (browser, CDN, application server, database). Use appropriate cache invalidation strategies (TTL, event-based). Consider cache coherence for distributed systems.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
1. Horizontal vs Vertical Partitioning:
Vertical partitioning splits tables by columns, often separating different features. Horizontal partitioning splits tables by rows, distributing data across multiple servers. Vertical organizes data logically, while horizontal improves scalability + performance.
2. Apache Kafka:
Kafka is a distributed streaming platform using a publish-subscribe model. It's fast due to the sequential disk I/O, zero-copy principle, and efficient batching of messages.
3. Rate Limiter:
A rate limiter controls the rate of requests a client can make to a service. It prevents overload and ensures fair resource usage.
4. JWT vs OAuth vs SAML:
JWT is a compact, self-contained token for secure information transmission. OAuth is an authorization framework for delegated access. SAML is an XML-based standard for exchanging authentication and authorization data.
5. Single Sign-On (SSO):
SSO allows users to access multiple applications with one set of credentials. It typically uses a central authentication server and protocols like SAML/OAuth.
6. Microservices vs Monolithic Architecture:
Microservices architecture breaks an application into small, independent services. Monolithic architecture is a single, tightly-coupled unit. Microservices offer scalability while monoliths are simpler to develop + deploy.
7. Reverse Proxy vs Forward Proxy:
A reverse proxy sits in front of web servers, forwarding client requests to backend servers. A forward proxy sits in front of clients, forwarding their requests to the internet. Reverse proxies are used for load balancing and security, while forward proxies are used for anonymity and filtering.
8. CAP Theorem:
The CAP theorem states that a distributed system can only provide two of three guarantees: Consistency, Availability, and Partition tolerance. In practice, partition tolerance is necessary, so systems must choose between consistency and availability during network partitions.
10. Efficient Caching Strategy:
Implement multi-level caching (browser, CDN, application server, database). Use appropriate cache invalidation strategies (TTL, event-based). Consider cache coherence for distributed systems.
Best DSA RESOURCES: https://topmate.io/coding/886874
All the best ๐๐
๐4โค1
Type of problem, while solving DSA problem in Array
โ There are many types of problems that can be solved using arrays and different techniques in Data Structures and Algorithms. Here are some common problem types and techniques that you might encounter:
๐. ๐๐ฅ๐ข๐๐ข๐ง๐ ๐ฐ๐ข๐ง๐๐จ๐ฐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are given an array and a window size, and you have to find a subarray of that size that satisfies certain conditions. You can use a sliding window technique to efficiently search through the array by maintaining a current window of fixed size and updating it as you move forward.
๐. ๐๐ฐ๐จ ๐ฉ๐จ๐ข๐ง๐ญ๐๐ซ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you use two pointers to traverse the array from both ends and find a certain pattern or condition. For example, you can use two pointers to find a pair of elements that sum up to a target value, or to reverse an array.
๐. ๐๐จ๐ซ๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to sort an array in a certain way, such as in ascending or descending order, or according to certain criteria such as frequency or value. You can use sorting algorithms such as merge sort or quick sort to efficiently sort the array.
๐. ๐๐๐๐ซ๐๐ก๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a specific element in the array or to search for a certain pattern. You can use searching algorithms such as binary search or linear search to efficiently search through the array.
๐. ๐๐ฎ๐๐๐ซ๐ซ๐๐ฒ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a contiguous subarray that satisfies certain conditions. You can use techniques such as prefix sum or Kadane's algorithm to efficiently find the subarray with the maximum sum.
๐. ๐๐จ๐ฎ๐ง๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to count the occurrences of certain elements or to count the number of subarrays or subsequences that satisfy certain conditions. You can use techniques such as hashing or dynamic programming to efficiently count the occurrences or number of subarrays.
โ There are many types of problems that can be solved using arrays and different techniques in Data Structures and Algorithms. Here are some common problem types and techniques that you might encounter:
๐. ๐๐ฅ๐ข๐๐ข๐ง๐ ๐ฐ๐ข๐ง๐๐จ๐ฐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are given an array and a window size, and you have to find a subarray of that size that satisfies certain conditions. You can use a sliding window technique to efficiently search through the array by maintaining a current window of fixed size and updating it as you move forward.
๐. ๐๐ฐ๐จ ๐ฉ๐จ๐ข๐ง๐ญ๐๐ซ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you use two pointers to traverse the array from both ends and find a certain pattern or condition. For example, you can use two pointers to find a pair of elements that sum up to a target value, or to reverse an array.
๐. ๐๐จ๐ซ๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to sort an array in a certain way, such as in ascending or descending order, or according to certain criteria such as frequency or value. You can use sorting algorithms such as merge sort or quick sort to efficiently sort the array.
๐. ๐๐๐๐ซ๐๐ก๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a specific element in the array or to search for a certain pattern. You can use searching algorithms such as binary search or linear search to efficiently search through the array.
๐. ๐๐ฎ๐๐๐ซ๐ซ๐๐ฒ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to find a contiguous subarray that satisfies certain conditions. You can use techniques such as prefix sum or Kadane's algorithm to efficiently find the subarray with the maximum sum.
๐. ๐๐จ๐ฎ๐ง๐ญ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ: In these problems, you are asked to count the occurrences of certain elements or to count the number of subarrays or subsequences that satisfy certain conditions. You can use techniques such as hashing or dynamic programming to efficiently count the occurrences or number of subarrays.
๐2โค1
How to master Python from scratch๐
1. Setup and Basics ๐
- Install Python ๐ฅ๏ธ: Download Python and set it up.
- Hello, World! ๐: Write your first Hello World program.
2. Basic Syntax ๐
- Variables and Data Types ๐: Learn about strings, integers, floats, and booleans.
- Control Structures ๐: Understand if-else statements, for loops, and while loops.
- Functions ๐ ๏ธ: Write reusable blocks of code.
3. Data Structures ๐
- Lists ๐: Manage collections of items.
- Dictionaries ๐: Store key-value pairs.
- Tuples ๐ฆ: Work with immutable sequences.
- Sets ๐ข: Handle collections of unique items.
4. Modules and Packages ๐ฆ
- Standard Library ๐: Explore built-in modules.
- Third-Party Packages ๐: Install and use packages with pip.
5. File Handling ๐
- Read and Write Files ๐
- CSV and JSON ๐
6. Object-Oriented Programming ๐งฉ
- Classes and Objects ๐๏ธ
- Inheritance and Polymorphism ๐จโ๐ฉโ๐ง
7. Web Development ๐
- Flask ๐ผ: Start with a micro web framework.
- Django ๐ฆ: Dive into a full-fledged web framework.
8. Data Science and Machine Learning ๐ง
- NumPy ๐: Numerical operations.
- Pandas ๐ผ: Data manipulation and analysis.
- Matplotlib ๐ and Seaborn ๐: Data visualization.
- Scikit-learn ๐ค: Machine learning.
9. Automation and Scripting ๐ค
- Automate Tasks ๐ ๏ธ: Use Python to automate repetitive tasks.
- APIs ๐: Interact with web services.
10. Testing and Debugging ๐
- Unit Testing ๐งช: Write tests for your code.
- Debugging ๐: Learn to debug efficiently.
11. Advanced Topics ๐
- Concurrency and Parallelism ๐
- Decorators ๐ and Generators โ๏ธ
- Web Scraping ๐ธ๏ธ: Extract data from websites using BeautifulSoup and Scrapy.
12. Practice Projects ๐ก
- Calculator ๐งฎ
- To-Do List App ๐
- Weather App โ๏ธ
- Personal Blog ๐
13. Community and Collaboration ๐ค
- Contribute to Open Source ๐
- Join Coding Communities ๐ฌ
- Participate in Hackathons ๐
14. Keep Learning and Improving ๐
- Read Books ๐: Like "Automate the Boring Stuff with Python".
- Watch Tutorials ๐ฅ: Follow video courses and tutorials.
- Solve Challenges ๐งฉ: On platforms like LeetCode, HackerRank, and CodeWars.
15. Teach and Share Knowledge ๐ข
- Write Blogs โ๏ธ
- Create Video Tutorials ๐น
- Mentor Others ๐จโ๐ซ
I have curated the best interview resources to crack Python Interviews ๐๐
https://topmate.io/coding/898340
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
1. Setup and Basics ๐
- Install Python ๐ฅ๏ธ: Download Python and set it up.
- Hello, World! ๐: Write your first Hello World program.
2. Basic Syntax ๐
- Variables and Data Types ๐: Learn about strings, integers, floats, and booleans.
- Control Structures ๐: Understand if-else statements, for loops, and while loops.
- Functions ๐ ๏ธ: Write reusable blocks of code.
3. Data Structures ๐
- Lists ๐: Manage collections of items.
- Dictionaries ๐: Store key-value pairs.
- Tuples ๐ฆ: Work with immutable sequences.
- Sets ๐ข: Handle collections of unique items.
4. Modules and Packages ๐ฆ
- Standard Library ๐: Explore built-in modules.
- Third-Party Packages ๐: Install and use packages with pip.
5. File Handling ๐
- Read and Write Files ๐
- CSV and JSON ๐
6. Object-Oriented Programming ๐งฉ
- Classes and Objects ๐๏ธ
- Inheritance and Polymorphism ๐จโ๐ฉโ๐ง
7. Web Development ๐
- Flask ๐ผ: Start with a micro web framework.
- Django ๐ฆ: Dive into a full-fledged web framework.
8. Data Science and Machine Learning ๐ง
- NumPy ๐: Numerical operations.
- Pandas ๐ผ: Data manipulation and analysis.
- Matplotlib ๐ and Seaborn ๐: Data visualization.
- Scikit-learn ๐ค: Machine learning.
9. Automation and Scripting ๐ค
- Automate Tasks ๐ ๏ธ: Use Python to automate repetitive tasks.
- APIs ๐: Interact with web services.
10. Testing and Debugging ๐
- Unit Testing ๐งช: Write tests for your code.
- Debugging ๐: Learn to debug efficiently.
11. Advanced Topics ๐
- Concurrency and Parallelism ๐
- Decorators ๐ and Generators โ๏ธ
- Web Scraping ๐ธ๏ธ: Extract data from websites using BeautifulSoup and Scrapy.
12. Practice Projects ๐ก
- Calculator ๐งฎ
- To-Do List App ๐
- Weather App โ๏ธ
- Personal Blog ๐
13. Community and Collaboration ๐ค
- Contribute to Open Source ๐
- Join Coding Communities ๐ฌ
- Participate in Hackathons ๐
14. Keep Learning and Improving ๐
- Read Books ๐: Like "Automate the Boring Stuff with Python".
- Watch Tutorials ๐ฅ: Follow video courses and tutorials.
- Solve Challenges ๐งฉ: On platforms like LeetCode, HackerRank, and CodeWars.
15. Teach and Share Knowledge ๐ข
- Write Blogs โ๏ธ
- Create Video Tutorials ๐น
- Mentor Others ๐จโ๐ซ
I have curated the best interview resources to crack Python Interviews ๐๐
https://topmate.io/coding/898340
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
๐4
Frontend Development Interview Questions
Beginner Level
1. What are semantic HTML tags?
2. Difference between id and class in HTML?
3. What is the Box Model in CSS?
4. Difference between margin and padding?
5. What is a responsive web design?
6. What is the use of the <meta viewport> tag?
7. Difference between inline, block, and inline-block elements?
8. What is the difference between == and === in JavaScript?
9. What are arrow functions in JavaScript?
10. What is DOM and how is it used?
Intermediate Level
1. What are pseudo-classes and pseudo-elements in CSS?
2. How do media queries work in responsive design?
3. Difference between relative, absolute, fixed, and sticky positioning?
4. What is the event loop in JavaScript?
5. Explain closures in JavaScript with an example.
6. What are Promises and how do you handle errors with .catch()?
7. What is a higher-order function?
8. What is the difference between localStorage and sessionStorage?
9. How does this keyword work in different contexts?
10. What is JSX in React?
Advanced Level
1. How does the virtual DOM work in React?
2. What are controlled vs uncontrolled components in React?
3. What is useMemo and when should you use it?
4. How do you optimize a large React app for performance?
5. What are React lifecycle methods (class-based) and their hook equivalents?
6. How does Redux work and when should you use it?
7. What is code splitting and why is it useful?
8. How do you secure a frontend app from XSS attacks?
9. Explain the concept of Server-Side Rendering (SSR) vs Client-Side Rendering (CSR).
10. What are Web Components and how do they work?
React โค๏ธ for the detailed answers
Join for free resources: ๐ https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
Beginner Level
1. What are semantic HTML tags?
2. Difference between id and class in HTML?
3. What is the Box Model in CSS?
4. Difference between margin and padding?
5. What is a responsive web design?
6. What is the use of the <meta viewport> tag?
7. Difference between inline, block, and inline-block elements?
8. What is the difference between == and === in JavaScript?
9. What are arrow functions in JavaScript?
10. What is DOM and how is it used?
Intermediate Level
1. What are pseudo-classes and pseudo-elements in CSS?
2. How do media queries work in responsive design?
3. Difference between relative, absolute, fixed, and sticky positioning?
4. What is the event loop in JavaScript?
5. Explain closures in JavaScript with an example.
6. What are Promises and how do you handle errors with .catch()?
7. What is a higher-order function?
8. What is the difference between localStorage and sessionStorage?
9. How does this keyword work in different contexts?
10. What is JSX in React?
Advanced Level
1. How does the virtual DOM work in React?
2. What are controlled vs uncontrolled components in React?
3. What is useMemo and when should you use it?
4. How do you optimize a large React app for performance?
5. What are React lifecycle methods (class-based) and their hook equivalents?
6. How does Redux work and when should you use it?
7. What is code splitting and why is it useful?
8. How do you secure a frontend app from XSS attacks?
9. Explain the concept of Server-Side Rendering (SSR) vs Client-Side Rendering (CSR).
10. What are Web Components and how do they work?
React โค๏ธ for the detailed answers
Join for free resources: ๐ https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
๐2
Leetcode patterns you should definitely checkout to Learn DSA(Java) from scratch
1๏ธโฃ Arrays: Data structures, such as arrays, store elements in contiguous memory locations. They are versatile and useful for a wide variety of purposes.
LeetCode Problems:
โข Search in Rotated Sorted Array (Problem #33)
โข Product of Array Except Self (Problem #238)
โข Find the Missing Number (Problem #268)
2๏ธโฃTwo Pointers: In Two Pointers, two pointers are maintained in the collection and can be manipulated to solve a problem efficiently.
LeetCode problems:
โข Trapping Rain Water (Problem #42)
โข Longest Substring Without Repeating Characters (Problem #3)
โข Squares of a Sorted Array (Problem #977)
3๏ธโฃIn-place Linked List Traversal: As an explanation, in-place traversal is a technique for modifying linked list nodes without using extra space.
LeetCode Problems:
โข Remove Nth Node From End of List (Problem #19)
โข Reorder List (Problem #143)
4๏ธโฃFast & Slow Pointers: This pattern uses two pointers to traverse a sequence at different speeds (fast and slow), often used to detect cycles or find a specific position in the sequence.
LeetCode Problems:
โข Happy Number (Problem #202)
โข Subarray Sum Equals K (Problem #560)
โข Intersection of Two Linked Lists (Problem #160)
5๏ธโฃMerge Intervals: This pattern involves merging overlapping intervals in a collection, often used in problems dealing with intervals or ranges.
LeetCode problems:
โข Non-overlapping Intervals (Problem #435)
โข Minimum Number of Arrows to Burst Balloons (Problem #452)
Join for more: https://t.me/crackingthecodinginterview
DSA Interview Preparation Resources: https://topmate.io/coding/886874
ENJOY LEARNING ๐๐
1๏ธโฃ Arrays: Data structures, such as arrays, store elements in contiguous memory locations. They are versatile and useful for a wide variety of purposes.
LeetCode Problems:
โข Search in Rotated Sorted Array (Problem #33)
โข Product of Array Except Self (Problem #238)
โข Find the Missing Number (Problem #268)
2๏ธโฃTwo Pointers: In Two Pointers, two pointers are maintained in the collection and can be manipulated to solve a problem efficiently.
LeetCode problems:
โข Trapping Rain Water (Problem #42)
โข Longest Substring Without Repeating Characters (Problem #3)
โข Squares of a Sorted Array (Problem #977)
3๏ธโฃIn-place Linked List Traversal: As an explanation, in-place traversal is a technique for modifying linked list nodes without using extra space.
LeetCode Problems:
โข Remove Nth Node From End of List (Problem #19)
โข Reorder List (Problem #143)
4๏ธโฃFast & Slow Pointers: This pattern uses two pointers to traverse a sequence at different speeds (fast and slow), often used to detect cycles or find a specific position in the sequence.
LeetCode Problems:
โข Happy Number (Problem #202)
โข Subarray Sum Equals K (Problem #560)
โข Intersection of Two Linked Lists (Problem #160)
5๏ธโฃMerge Intervals: This pattern involves merging overlapping intervals in a collection, often used in problems dealing with intervals or ranges.
LeetCode problems:
โข Non-overlapping Intervals (Problem #435)
โข Minimum Number of Arrows to Burst Balloons (Problem #452)
Join for more: https://t.me/crackingthecodinginterview
DSA Interview Preparation Resources: https://topmate.io/coding/886874
ENJOY LEARNING ๐๐
โค2๐2
Ages of Operating Systems๐จ๐ปโ๐ป๐
๐ Windows 11 (3 years old)
๐ช Windows 10 (8 years old)
๐ macOS Yosemite (10 years old)
๐ Kali Linux (11 years old)
๐ป Windows 8 (12 years old)
๐ Manjaro (11 years old)
๐ป Windows 7 (14 years old)
๐ฅ๏ธ Windows Vista (17 years old)
๐ฟ Linux Mint (18 years old)
๐ง Ubuntu (20 years old)
โ๏ธ Fedora (20 years old)
๐ง OpenSUSE (20 years old)
โ๏ธ CentOS (20 years old)
๐ง Arch Linux (22 years old)
๐ macOS (22 years old)
๐ป Windows XP (23 years old)
๐ฅ๏ธ Windows 2000 (24 years old)
๐ฑ Windows 98 (25 years old)
๐ Windows 95 (28 years old)
๐ป Windows 3.1 (29 years old)
๐ฅ๏ธ OS/2 (32 years old)
๐ง Debian (31 years old)
๐ด Red Hat Linux (30 years old)
๐ฎ AmigaOS (34 years old)
๐ฅ๏ธ Xenix (40 years old)
๐ VMS (44 years old)
๐พ MS-DOS (42 years old)
๐พ CP/M (49 years old)
๐ฅ๏ธ Unix (54 years old)
๐ Windows 11 (3 years old)
๐ช Windows 10 (8 years old)
๐ macOS Yosemite (10 years old)
๐ Kali Linux (11 years old)
๐ป Windows 8 (12 years old)
๐ Manjaro (11 years old)
๐ป Windows 7 (14 years old)
๐ฅ๏ธ Windows Vista (17 years old)
๐ฟ Linux Mint (18 years old)
๐ง Ubuntu (20 years old)
โ๏ธ Fedora (20 years old)
๐ง OpenSUSE (20 years old)
โ๏ธ CentOS (20 years old)
๐ง Arch Linux (22 years old)
๐ macOS (22 years old)
๐ป Windows XP (23 years old)
๐ฅ๏ธ Windows 2000 (24 years old)
๐ฑ Windows 98 (25 years old)
๐ Windows 95 (28 years old)
๐ป Windows 3.1 (29 years old)
๐ฅ๏ธ OS/2 (32 years old)
๐ง Debian (31 years old)
๐ด Red Hat Linux (30 years old)
๐ฎ AmigaOS (34 years old)
๐ฅ๏ธ Xenix (40 years old)
๐ VMS (44 years old)
๐พ MS-DOS (42 years old)
๐พ CP/M (49 years old)
๐ฅ๏ธ Unix (54 years old)
โค2๐2
10 Must-Have Tools for Web Developers in 2025
โ Visual Studio Code โ The go-to lightweight and powerful code editor
โ Figma โ Design UI/UX prototypes and collaborate visually with your team
โ Chrome DevTools โ Inspect, debug, and optimize performance in real-time
โ GitHub โ Host your code, collaborate, and manage projects seamlessly
โ Postman โ Test and manage APIs like a pro
โ Tailwind CSS โ Build sleek, responsive UIs with utility-first classes
โ Vite โ Superfast front-end build tool and dev server
โ React Developer Tools โ Debug React components directly in your browser
โ ESLint + Prettier โ Keep your code clean, consistent, and error-free
โ Netlify โ Deploy your front-end apps in seconds with CI/CD integration
React if you're building cool stuff on the web!
Web Development Resources โฌ๏ธ
https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
ENJOY LEARNING ๐๐
#webdevelopment
โ Visual Studio Code โ The go-to lightweight and powerful code editor
โ Figma โ Design UI/UX prototypes and collaborate visually with your team
โ Chrome DevTools โ Inspect, debug, and optimize performance in real-time
โ GitHub โ Host your code, collaborate, and manage projects seamlessly
โ Postman โ Test and manage APIs like a pro
โ Tailwind CSS โ Build sleek, responsive UIs with utility-first classes
โ Vite โ Superfast front-end build tool and dev server
โ React Developer Tools โ Debug React components directly in your browser
โ ESLint + Prettier โ Keep your code clean, consistent, and error-free
โ Netlify โ Deploy your front-end apps in seconds with CI/CD integration
React if you're building cool stuff on the web!
Web Development Resources โฌ๏ธ
https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
ENJOY LEARNING ๐๐
#webdevelopment
โค3
Essential Topics to Master Data Science Interviews: ๐
SQL:
1. Foundations
- Craft SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING
- Embrace Basic JOINS (INNER, LEFT, RIGHT, FULL)
- Navigate through simple databases and tables
2. Intermediate SQL
- Utilize Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- Embrace Subqueries and nested queries
- Master Common Table Expressions (WITH clause)
- Implement CASE statements for logical queries
3. Advanced SQL
- Explore Advanced JOIN techniques (self-join, non-equi join)
- Dive into Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)
- Optimize queries with indexing
- Execute Data manipulation (INSERT, UPDATE, DELETE)
Python:
1. Python Basics
- Grasp Syntax, variables, and data types
- Command Control structures (if-else, for and while loops)
- Understand Basic data structures (lists, dictionaries, sets, tuples)
- Master Functions, lambda functions, and error handling (try-except)
- Explore Modules and packages
2. Pandas & Numpy
- Create and manipulate DataFrames and Series
- Perfect Indexing, selecting, and filtering data
- Handle missing data (fillna, dropna)
- Aggregate data with groupby, summarizing data
- Merge, join, and concatenate datasets
3. Data Visualization with Python
- Plot with Matplotlib (line plots, bar plots, histograms)
- Visualize with Seaborn (scatter plots, box plots, pair plots)
- Customize plots (sizes, labels, legends, color palettes)
- Introduction to interactive visualizations (e.g., Plotly)
Excel:
1. Excel Essentials
- Conduct Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)
- Dive into charts and basic data visualization
- Sort and filter data, use Conditional formatting
2. Intermediate Excel
- Master Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)
- Leverage PivotTables and PivotCharts for summarizing data
- Utilize data validation tools
- Employ What-if analysis tools (Data Tables, Goal Seek)
3. Advanced Excel
- Harness Array formulas and advanced functions
- Dive into Data Model & Power Pivot
- Explore Advanced Filter, Slicers, and Timelines in Pivot Tables
- Create dynamic charts and interactive dashboards
Power BI:
1. Data Modeling in Power BI
- Import data from various sources
- Establish and manage relationships between datasets
- Grasp Data modeling basics (star schema, snowflake schema)
2. Data Transformation in Power BI
- Use Power Query for data cleaning and transformation
- Apply advanced data shaping techniques
- Create Calculated columns and measures using DAX
3. Data Visualization and Reporting in Power BI
- Craft interactive reports and dashboards
- Utilize Visualizations (bar, line, pie charts, maps)
- Publish and share reports, schedule data refreshes
Statistics Fundamentals:
- Mean, Median, Mode
- Standard Deviation, Variance
- Probability Distributions, Hypothesis Testing
- P-values, Confidence Intervals
- Correlation, Simple Linear Regression
- Normal Distribution, Binomial Distribution, Poisson Distribution.
Show some โค๏ธ if you're ready to elevate your data science game! ๐
ENJOY LEARNING ๐๐
SQL:
1. Foundations
- Craft SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING
- Embrace Basic JOINS (INNER, LEFT, RIGHT, FULL)
- Navigate through simple databases and tables
2. Intermediate SQL
- Utilize Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- Embrace Subqueries and nested queries
- Master Common Table Expressions (WITH clause)
- Implement CASE statements for logical queries
3. Advanced SQL
- Explore Advanced JOIN techniques (self-join, non-equi join)
- Dive into Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)
- Optimize queries with indexing
- Execute Data manipulation (INSERT, UPDATE, DELETE)
Python:
1. Python Basics
- Grasp Syntax, variables, and data types
- Command Control structures (if-else, for and while loops)
- Understand Basic data structures (lists, dictionaries, sets, tuples)
- Master Functions, lambda functions, and error handling (try-except)
- Explore Modules and packages
2. Pandas & Numpy
- Create and manipulate DataFrames and Series
- Perfect Indexing, selecting, and filtering data
- Handle missing data (fillna, dropna)
- Aggregate data with groupby, summarizing data
- Merge, join, and concatenate datasets
3. Data Visualization with Python
- Plot with Matplotlib (line plots, bar plots, histograms)
- Visualize with Seaborn (scatter plots, box plots, pair plots)
- Customize plots (sizes, labels, legends, color palettes)
- Introduction to interactive visualizations (e.g., Plotly)
Excel:
1. Excel Essentials
- Conduct Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)
- Dive into charts and basic data visualization
- Sort and filter data, use Conditional formatting
2. Intermediate Excel
- Master Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)
- Leverage PivotTables and PivotCharts for summarizing data
- Utilize data validation tools
- Employ What-if analysis tools (Data Tables, Goal Seek)
3. Advanced Excel
- Harness Array formulas and advanced functions
- Dive into Data Model & Power Pivot
- Explore Advanced Filter, Slicers, and Timelines in Pivot Tables
- Create dynamic charts and interactive dashboards
Power BI:
1. Data Modeling in Power BI
- Import data from various sources
- Establish and manage relationships between datasets
- Grasp Data modeling basics (star schema, snowflake schema)
2. Data Transformation in Power BI
- Use Power Query for data cleaning and transformation
- Apply advanced data shaping techniques
- Create Calculated columns and measures using DAX
3. Data Visualization and Reporting in Power BI
- Craft interactive reports and dashboards
- Utilize Visualizations (bar, line, pie charts, maps)
- Publish and share reports, schedule data refreshes
Statistics Fundamentals:
- Mean, Median, Mode
- Standard Deviation, Variance
- Probability Distributions, Hypothesis Testing
- P-values, Confidence Intervals
- Correlation, Simple Linear Regression
- Normal Distribution, Binomial Distribution, Poisson Distribution.
Show some โค๏ธ if you're ready to elevate your data science game! ๐
ENJOY LEARNING ๐๐
๐2
Learn for free:
HTML: html.com
CSS: web.dev/learn/css
JavaScript: t.me/javascript_courses
React: react-tutorial.app
API: rapidapi.com/learn
Python: t.me/pythonanalyst
SQL: t.me/sqlanalyst
Git: git-scm.com/book
HTML: html.com
CSS: web.dev/learn/css
JavaScript: t.me/javascript_courses
React: react-tutorial.app
API: rapidapi.com/learn
Python: t.me/pythonanalyst
SQL: t.me/sqlanalyst
Git: git-scm.com/book
๐1
Problem: Given an array a of n integers, find all such elements a[i], a[j], a[k], and a[l], such that a[i] + a[j] + a[k] + a[l] = target? Output all unique quadruples.
Solution: of course one way would be to just use 4 nested loops to iterate over all possible quadruples, but this is quite slow O(n^4). Another way is to iterate over all triples, put the sums into a set and then in another pass over elements a[i] check if we have any triple with sum (T - a[i]). This would give us O(n^3), and we need to keep track of which elements gave us the required sums. Another step is to iterate over all pairs and put results into a map from integer to indexes of elements, which produce this sum. Then in another pass over this map we can see if we can get a sum of T using two different values from the map (and they shouldn't be using the same element twice). This approach has time complexity O(n^2).
Solution: of course one way would be to just use 4 nested loops to iterate over all possible quadruples, but this is quite slow O(n^4). Another way is to iterate over all triples, put the sums into a set and then in another pass over elements a[i] check if we have any triple with sum (T - a[i]). This would give us O(n^3), and we need to keep track of which elements gave us the required sums. Another step is to iterate over all pairs and put results into a map from integer to indexes of elements, which produce this sum. Then in another pass over this map we can see if we can get a sum of T using two different values from the map (and they shouldn't be using the same element twice). This approach has time complexity O(n^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.me/free4unow_backup
All the best ๐๐
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.me/free4unow_backup
All the best ๐๐
๐2
Guys, Big Announcement!
Weโve officially hit 2 MILLION followers โ and itโs time to take our Python journey to the next level!
Iโm super excited to launch the 30-Day Python Coding Challenge โ perfect for absolute beginners, interview prep, or anyone wanting to build real projects from scratch.
This challenge is your daily dose of Python โ bite-sized lessons with hands-on projects so you actually code every day and level up fast.
Hereโs what youโll learn over the next 30 days:
Week 1: Python Fundamentals
- Variables & Data Types (Build your own bio/profile script)
- Operators (Mini calculator to sharpen math skills)
- Strings & String Methods (Word counter & palindrome checker)
- Lists & Tuples (Manage a grocery list like a pro)
- Dictionaries & Sets (Create your own contact book)
- Conditionals (Make a guess-the-number game)
- Loops (Multiplication tables & pattern printing)
Week 2: Functions & Logic โ Make Your Code Smarter
- Functions (Prime number checker)
- Function Arguments (Tip calculator with custom tips)
- Recursion Basics (Factorials & Fibonacci series)
- Lambda, map & filter (Process lists efficiently)
- List Comprehensions (Filter odd/even numbers easily)
- Error Handling (Build a safe input reader)
- Review + Mini Project (Command-line to-do list)
Week 3: Files, Modules & OOP
- Reading & Writing Files (Save and load notes)
- Custom Modules (Create your own utility math module)
- Classes & Objects (Student grade tracker)
- Inheritance & OOP (RPG character system)
- Dunder Methods (Build a custom string class)
- OOP Mini Project (Simple bank account system)
- Review & Practice (Quiz app using OOP concepts)
Week 4: Real-World Python & APIs โ Build Cool Apps
- JSON & APIs (Fetch weather data)
- Web Scraping (Extract titles from HTML)
- Regular Expressions (Find emails & phone numbers)
- Tkinter GUI (Create a simple counter app)
- CLI Tools (Command-line calculator with argparse)
- Automation (File organizer script)
- Final Project (Choose, build, and polish your app!)
React with โค๏ธ if you're ready for this new journey
You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1661
Weโve officially hit 2 MILLION followers โ and itโs time to take our Python journey to the next level!
Iโm super excited to launch the 30-Day Python Coding Challenge โ perfect for absolute beginners, interview prep, or anyone wanting to build real projects from scratch.
This challenge is your daily dose of Python โ bite-sized lessons with hands-on projects so you actually code every day and level up fast.
Hereโs what youโll learn over the next 30 days:
Week 1: Python Fundamentals
- Variables & Data Types (Build your own bio/profile script)
- Operators (Mini calculator to sharpen math skills)
- Strings & String Methods (Word counter & palindrome checker)
- Lists & Tuples (Manage a grocery list like a pro)
- Dictionaries & Sets (Create your own contact book)
- Conditionals (Make a guess-the-number game)
- Loops (Multiplication tables & pattern printing)
Week 2: Functions & Logic โ Make Your Code Smarter
- Functions (Prime number checker)
- Function Arguments (Tip calculator with custom tips)
- Recursion Basics (Factorials & Fibonacci series)
- Lambda, map & filter (Process lists efficiently)
- List Comprehensions (Filter odd/even numbers easily)
- Error Handling (Build a safe input reader)
- Review + Mini Project (Command-line to-do list)
Week 3: Files, Modules & OOP
- Reading & Writing Files (Save and load notes)
- Custom Modules (Create your own utility math module)
- Classes & Objects (Student grade tracker)
- Inheritance & OOP (RPG character system)
- Dunder Methods (Build a custom string class)
- OOP Mini Project (Simple bank account system)
- Review & Practice (Quiz app using OOP concepts)
Week 4: Real-World Python & APIs โ Build Cool Apps
- JSON & APIs (Fetch weather data)
- Web Scraping (Extract titles from HTML)
- Regular Expressions (Find emails & phone numbers)
- Tkinter GUI (Create a simple counter app)
- CLI Tools (Command-line calculator with argparse)
- Automation (File organizer script)
- Final Project (Choose, build, and polish your app!)
React with โค๏ธ if you're ready for this new journey
You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1661
โค1๐1
Web Development Mastery: From Basics to Advanced ๐
Start with the fundamentals:
- HTML
- CSS
- JavaScript
- Responsive Design
- Basic DOM Manipulation
- Git and Version Control
You can grasp these essentials in just a week.
Once you're comfortable, dive into intermediate topics:
- AJAX
- APIs
- Frameworks like React, Angular, or Vue
- Front-end Build Tools (Webpack, Babel)
- Back-end basics with Node.js, Express, or Django
Take another week to solidify these skills.
Ready for the advanced level? Explore:
- Authentication and Authorization
- RESTful APIs
- GraphQL
- WebSockets
- Docker and Containerization
- Testing (Unit, Integration, E2E)
These advanced concepts can be mastered in a couple of weeks.
Remember, mastery comes with practice:
- Create a simple web project
- Tackle an intermediate-level project
- Challenge yourself with an advanced project involving complex features
Consistent practice is the key to becoming a web development pro.
Best platforms to learn:
- FreeCodeCamp
- Web Development Free Courses
- Web Development Roadmap
- Projects
- Bootcamp
Share your progress and learnings with others in the community. Enjoy the journey! ๐ฉโ๐ป๐จโ๐ป
Join @free4unow_backup for more free resources.
Like this post if it helps ๐โค๏ธ
ENJOY LEARNING ๐๐
Start with the fundamentals:
- HTML
- CSS
- JavaScript
- Responsive Design
- Basic DOM Manipulation
- Git and Version Control
You can grasp these essentials in just a week.
Once you're comfortable, dive into intermediate topics:
- AJAX
- APIs
- Frameworks like React, Angular, or Vue
- Front-end Build Tools (Webpack, Babel)
- Back-end basics with Node.js, Express, or Django
Take another week to solidify these skills.
Ready for the advanced level? Explore:
- Authentication and Authorization
- RESTful APIs
- GraphQL
- WebSockets
- Docker and Containerization
- Testing (Unit, Integration, E2E)
These advanced concepts can be mastered in a couple of weeks.
Remember, mastery comes with practice:
- Create a simple web project
- Tackle an intermediate-level project
- Challenge yourself with an advanced project involving complex features
Consistent practice is the key to becoming a web development pro.
Best platforms to learn:
- FreeCodeCamp
- Web Development Free Courses
- Web Development Roadmap
- Projects
- Bootcamp
Share your progress and learnings with others in the community. Enjoy the journey! ๐ฉโ๐ป๐จโ๐ป
Join @free4unow_backup for more free resources.
Like this post if it helps ๐โค๏ธ
ENJOY LEARNING ๐๐
๐2โค1