Web Development Interview Questions Part-2

11. What are semantic HTML elements?
Answer:
Semantic elements clearly describe their meaning in a human- and machine-readable way. Examples: <header>, <footer>, <article>, <nav>.

12. What are HTTP status codes?
Answer:
They indicate the result of an HTTP request.
Common ones:

200 OK (Success)

404 Not Found

500 Internal Server Error

401 Unauthorized

403 Forbidden


13. What is the box model in CSS?
Answer:
The box model includes:

Content

Padding

Border

Margin
It defines how space is taken up around HTML elements.


14. What are pseudo-classes in CSS?
Answer:
Pseudo-classes style elements based on their state.
Examples:

:hover (when mouse is over)

:first-child

:nth-child()


15. How do you make a website SEO-friendly?
Answer:

Use semantic HTML

Add meta tags and alt text

Mobile responsiveness

Fast loading speed

Proper URL structure


16. What is the difference between synchronous and asynchronous in JavaScript?
Answer:

Synchronous: Code runs line by line

Asynchronous: Tasks like API calls don't block other code; use callbacks, promises, or async/await


17. What is a promise in JavaScript?
Answer:
A Promise represents the result of an async operation.
It can be:

Pending

Fulfilled

Rejected


18. What is event bubbling and capturing in JavaScript?
Answer:

Bubbling: Event propagates from child to parent

Capturing: Event goes from parent to child
You can control it using event.stopPropagation()


19. What is a CDN?
Answer:
CDN (Content Delivery Network) delivers static files (images, CSS, JS) via servers closest to the user to improve website speed.

20. What tools do you use for version control?
Answer:
Most common: Git + GitHub
Git tracks changes in code, and GitHub helps you collaborate and manage versions.

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SQL can be simple—if you learn it the smart way..



If you’re aiming to become a data analyst, mastering SQL is non-negotiable.
Here’s a smart roadmap to ace it:

1. Basics First: Understand data types, simple queries (SELECT, FROM, WHERE). Master basic filtering.

2. Joins & Relationships: Dive into INNER, LEFT, RIGHT joins. Practice combining tables to extract meaningful insights.

3. Aggregations & Functions: Get comfortable with COUNT, SUM, AVG, MAX, GROUP BY, and HAVING clauses. These are essential for summarizing data.

4. Subqueries & Nested Queries: Learn how to query within queries. This is powerful for handling complex datasets.

5. Window Functions: Explore ranking, cumulative sums, and sliding windows to work with running totals and moving averages.

6. Optimization: Study indexing and query optimization for faster, more efficient queries.

7. Real-World Scenarios: Apply your SQL knowledge to solve real-world business problems.

The journey may seem tough, but each step sharpens your skills and brings you closer to data analysis excellence. Stay consistent, practice regularly, and let SQL become your superpower! 💪

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💡 Tips to Crack Top Tech Companies using LeetCode 💻

Are you aiming to crack top tech companies? Here are some tips on how to effectively use the LeetCode platform to enhance your problem-solving skills and increase your chances of success:

1️⃣ Quality > Quantity ✅

Rather than focusing on solving a large number of problems, prioritize the quality of your solutions. It's better to solve a particular Data Structures and Algorithms (DSA) sheet thoroughly and revise it until you can build up the logic on your own. Consider using resources like the Striver Sheet or Grind 75 to guide your practice.

2️⃣ Maintain an Error Sheet ✅

Create an error sheet to keep track of the questions you've solved and the mistakes you've made while solving them. By reviewing this sheet regularly, you can identify common errors and strive to avoid repeating them. This practice will significantly improve your problem-solving skills over time.

3️⃣ Solve Top Interview Questions ✅

When preparing for a specific company's interview, focus on solving recent LeetCode questions that are tagged with that company's name. This way, you'll be familiar with the types of problems the company typically asks and be better prepared for the interview.

4️⃣ For Beginners ✅

If you're new to problem-solving, it's advisable to start with Easy-level problems before moving on to Medium or Hard ones. Aim to solve at least 25 problems in the Easy category before challenging yourself with more complex ones. This approach helps build a strong foundation and boosts your confidence.

5️⃣ Practice Weak Topics Regularly ✅

Identify the topics or problem types that you find challenging or fear the most. For example, if you struggle with graph problems, make it a habit to solve at least one graph problem every day. Regular practice in your weaker areas will help you improve your skills and boost your overall performance.

6️⃣ Don't Ignore Acceptance Level ✅

When browsing problems on LeetCode, consider sorting them by acceptance level. Prioritizing problems with a higher acceptance rate increases the likelihood of successfully solving them. This strategy allows you to build confidence by tackling problems that have been well-received by other users.

7️⃣ Don't Ignore Other Solutions ✅

Even if your solution is correct and accepted, don't overlook the opportunity to learn from others. Explore alternative solutions to the same problem. This practice exposes you to different approaches, algorithms, and optimizations, enabling you to discover new and efficient ways of solving problems.

8️⃣ Consistency is the Key ✅

Maintain a consistent practice schedule to make steady progress. Dedicate a block of time, such as 2-3 hours each day, to solve LeetCode problems. Additionally, set aside a specific day, like Saturdays, for weekly revisions. Consistency and regular practice will sharpen your problem-solving skills and increase your chances of cracking top tech company interviews.

Good luck with your LeetCode journey! 🚀

Learning Python in 2025 is like discovering a treasure chest 🎁 full of magical powers! Here's why it's valuable:

1. Versatility 🌟: Python is used in web development, data analysis, artificial intelligence, machine learning, automation, and more. Whatever your interest, Python has an option for it.

2. Ease of Learning 📚: Python's syntax is as clear as a sunny day!☀️ Its simple and readable syntax makes it beginner-friendly, perfect for aspiring programmers of all levels.

3. Community Support 🤝: Python has a vast community of programmers ready to help! Whether you're stuck on a problem or looking for guidance, there are countless forums, tutorials, and resources to tap into.

4. Job Opportunities 💼: Companies are constantly seeking Python wizards to join their ranks! From tech giants to startups, the demand for Python skills is abundant.🔥

5. Future-proofing 🔮: With its widespread adoption and continuous growth, learning Python now sets you up for success in the ever-evolving world of tech.

6. Fun Projects 🎉: Python makes coding feel like brewing potions! From creating games 🎮 to building robots 🤖, the possibilities are endless.

So grab your keyboard and embark on a Python adventure! It's not just learning a language, it's unlocking a world of endless possibilities.

🚀 Learn API development with Python

🔑 Core Skills Before API Development

Python Fundamentals
- Functions, classes, error handling
- JSON handling (json module)
- Virtual environments (venv, pipenv, or poetry)

HTTP Basics
- What is an API? (REST, GraphQL, gRPC basics)
- HTTP methods: GET, POST, PUT, PATCH, DELETE
- Status codes: 200, 201, 400, 401, 404, 500


🛠️ API Development with Python

1. Frameworks
- Flask (lightweight, easy for beginners)
- FastAPI (modern, async, automatic docs with Swagger/OpenAPI – highly recommended)
- Django REST Framework (DRF) (for large apps with Django)
👉 Start with FastAPI if your goal is modern, production-ready APIs.

2. Core Concepts
- Routing (endpoints like /users, /products)
- Path & query parameters
- Request & response handling (JSON input/output)
- Middleware (logging, authentication, error handling)


3. Data & Persistence
- Working with databases:
- SQL (PostgreSQL, MySQL, SQLite)
- ORMs: SQLAlchemy or Django ORM
- CRUD operations with database integration


4. Authentication & Security
- JWT (JSON Web Tokens)
- OAuth2 (Google, GitHub login)
- API key-based authentication
- CORS handling


5. Testing & Documentation
- Writing tests with pytest or unittest
- Automatic API docs (FastAPI auto-generates Swagger UI)
- Postman or cURL for testing endpoints


6. Deployment & Scaling
- Running APIs with Uvicorn or Gunicorn
- Containerization with Docker
- CI/CD (GitHub Actions, GitLab CI)
- Cloud deployment (AWS, GCP, Azure, or Heroku)


📚 Suggested Learning Path:
Learn FastAPI → build a simple "To-Do API"
Connect a database → PostgreSQL + SQLAlchemy
Add authentication → JWT-based login
Write tests → pytest for endpoints
Deploy on Docker + Cloud

Type of problem, while solving DSA problem in Array

❗ 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:

𝟏. 𝐒𝐥𝐢𝐝𝐢𝐧𝐠 𝐰𝐢𝐧𝐝𝐨𝐰 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: 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.

𝟐. 𝐓𝐰𝐨 𝐩𝐨𝐢𝐧𝐭𝐞𝐫 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: 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.

𝟑. 𝐒𝐨𝐫𝐭𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: 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.


𝟒. 𝐒𝐞𝐚𝐫𝐜𝐡𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: 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.

𝟓. 𝐒𝐮𝐛𝐚𝐫𝐫𝐚𝐲 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: 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.


𝟔. 𝐂𝐨𝐮𝐧𝐭𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: 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.

Big O Cheatsheet

Best Resources for Tech Interviews

Bookmark these sites FOREVER!!!

❯ HTML ➟ learn-html
❯ CSS ➟ css-tricks
❯ JavaScript ➟ javascript .info
❯ Python ➟ realpython
❯ C ➟ learn-c
❯ C++ ➟ fluentcpp
❯ Java ➟ baeldung
❯ SQL ➟ sqlbolt
❯ Go ➟ learn-golang
❯ Kotlin ➟ studytonight
❯ Swift ➟ codewithchris
❯ C# ➟ learncs
❯ PHP ➟ learn-php
❯ DSA ➟ techdevguide .withgoogle