Coding Interview Resources

10 Python Libraries for Building LLM Applications 🔹 1. Transformers Core library for loading, fine-tuning, and running LLMs with ease. 👉 Learn more: https://huggingface.co/docs/transformers 🔹 2. LangChain Connect prompts, tools, APIs, and models into powerful workflows. 👉 Learn more: https://docs.langchain.com 🔹 3. LlamaIndex Bring your own data into LLMs for smarter, grounded responses (RAG). 👉 Learn more: https://docs.llamaindex.ai 🔹 4. vLLM High-performance LLM serving with faster inference and better scaling. 👉 Learn more: https://docs.vllm.ai 🔹 5. Unsloth Efficient fine-tuning with LoRA & QLoRA — even on limited hardware. 👉 Learn more: https://github.com/unslothai/unsloth 🔹 6. CrewAI Build multi-agent systems where AI agents collaborate on tasks. 👉 Learn more: https://docs.crewai.com 🔹 7. AutoGPT Create goal-driven autonomous agents with step-by-step execution. 👉 Learn more: https://github.com/Significant-Gravitas/AutoGPT 🔹 8. LangGraph Design advanced, stateful workflows with branching logic. 👉 Learn more: https://docs.langchain.com/langgraph 🔹 9. DeepEval Test and evaluate LLM outputs for accuracy and reliability. 👉 Learn more: https://github.com/confident-ai/deepeval 🔹 10. OpenAI Python SDK Quickly integrate powerful AI features without managing infrastructure. 👉 Learn more: https://platform.openai.com/docs ❤️ Follow  for more

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🚀 𝗖𝗶𝘀𝗰𝗼 𝗙𝗥𝗘𝗘 𝗧𝗲𝗰𝗵 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 | 𝟱 𝗠𝘂𝘀𝘁-𝗗𝗼 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 🎓 Cisco offers learning opportunities covering some of the most valuable foundations for careers in Cybersecurity, Networking, Linux and IoT. ✅ Beginner-Friendly Tech Skills ✅ Learn In-Demand IT Concepts ✅ Build Practical Knowledge ✅ Strengthen Your Resume ✅ Great for Students & Freshers 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:-  https://pdlink.in/4fhCSKo 🔥 Learn from Cisco • Build Skills • Upgrade Your Resume • Get Career-Ready!

🚀 Top 100 JavaScript Interview Questions 📘 1. JavaScript Fundamentals (1–20) 1. What is JavaScript? 2. What are the different data types in JavaScript? 3. What is the difference between "var", "let", and "const"? 4. What are primitive and non-primitive data types? 5. What is type coercion? 6. What is the difference between "==" and "==="? 7. What are truthy and falsy values? 8. What is "undefined"? 9. What is "null"? 10. What is "NaN"? 11. What is the "typeof" operator? 12. What are template literals? 13. What are JavaScript operators? 14. What are ternary operators? 15. What is variable hoisting? 16. What is scope in JavaScript? 17. What are global, function, and block scope? 18. What is strict mode ("use strict")? 19. What are comments in JavaScript? 20. What are JavaScript modules? 📗 2. Functions & Objects (21–40) 1. What is a function? 2. What is a function expression? 3. What are arrow functions? 4. What is an IIFE (Immediately Invoked Function Expression)? 5. What are callback functions? 6. What are higher-order functions? 7. What are closures? 8. What is lexical scope? 9. What is the "this" keyword? 10. What are object literals? 11. How do you create objects in JavaScript? 12. What is object destructuring? 13. What is the spread operator (...)? 14. What is the rest operator? 15. What are default parameters? 16. What is optional chaining (?.)? 17. What is nullish coalescing (??)? 18. What are object methods? 19. What is method chaining? 20. What is object freezing and sealing? 📙 3. Arrays & ES6+ (41–60) 1. How do arrays work in JavaScript? 2. What is the difference between "map()" and "forEach()"? 3. What is "filter()"? 4. What is "reduce()"? 5. What is "find()"? 6. What is "findIndex()"? 7. What is "some()"? 8. What is "every()"? 9. What is the difference between "slice()" and "splice()"? 10. What are "push()", "pop()", "shift()", and "unshift()"? 11. How do you sort arrays? 12. What is array destructuring? 13. What are Sets? 14. What are Maps? 15. What are Symbols? 16. What are generators? 17. What are iterators? 18. What is destructuring assignment? 19. What is dynamic import? 20. What are ES6 modules? 📕 4. Asynchronous JavaScript (61–80) 1. What is asynchronous programming? 2. What is the event loop? 3. What is the call stack? 4. What is the callback queue? 5. What are Promises? 6. What are the states of a Promise? 7. What is "async/await"? 8. What is "Promise.all()"? 9. What is "Promise.race()"? 10. What is "Promise.allSettled()"? 11. What is "fetch()"? 12. What is AJAX? 13. What are Web APIs? 14. What is "setTimeout()"? 15. What is "setInterval()"? 16. What is "clearTimeout()"? 17. What is "clearInterval()"? 18. What is callback hell? 19. How do you avoid callback hell? 20. What are microtasks and macrotasks? 💡 5. DOM, Browser & Advanced Concepts (81–100) 1. What is the DOM? 2. How do you select DOM elements? 3. What is event bubbling? 4. What is event capturing? 5. What is event delegation? 6. What is the difference between "preventDefault()" and "stopPropagation()"? 87. What is localStorage? 88. What is sessionStorage? 89. What are cookies? 90. What is debouncing? 91. What is throttling? 92. What is memoization? 93. What is currying? 94. What is prototype inheritance? 95. What is prototypal inheritance? 96. What are classes in JavaScript? 97. What is garbage collection? 98. How does JavaScript manage memory? 99. What are CommonJS and ES Modules? 100. What are the latest JavaScript features introduced in ES2025 and beyond? Double Tap ❤️ For Detailed Answers ----- 1.29 ₽ · /balance_help

✅ Coding Acronyms You MUST Know – Part 2 💻🔥 OOP → Object-Oriented Programming SOLID → Five Object-Oriented Design Principles DRY → Don't Repeat Yourself KISS → Keep It Simple, Stupid YAGNI → You Aren't Gonna Need It IDE → Integrated Development Environment SDK → Software Development Kit JDK → Java Development Kit JRE → Java Runtime Environment JVM → Java Virtual Machine CLR → Common Language Runtime (.NET) GC → Garbage Collection HTTP → HyperText Transfer Protocol HTTPS → HyperText Transfer Protocol Secure SSL → Secure Sockets Layer TLS → Transport Layer Security SSH → Secure Shell FTP → File Transfer Protocol SFTP → Secure File Transfer Protocol SMTP → Simple Mail Transfer Protocol POP3 → Post Office Protocol Version 3 IMAP → Internet Message Access Protocol JSON → JavaScript Object Notation XML → eXtensible Markup Language CSV → Comma-Separated Values 💬 Double Tap ❤️ for more!

𝗔𝗜 & 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 (𝗡𝗼 𝗖𝗼𝗱𝗶𝗻𝗴 𝗡𝗲𝗲𝗱𝗲𝗱) Apply Now👉:- https://pdlink.in/4aYWald By E&ICT Academy, IIT Roorkee Batch Closing Soon - 26th July 2026

How to send follow up email to a recruiter 👇👇 Dear [Recruiter’s Name], I hope this email finds you doing well. I wanted to take a moment to express my sincere gratitude for the time and consideration you have given me throughout the recruitment process for the [position] role at [company]. I understand that you must be extremely busy and receive countless applications, so I wanted to reach out and follow up on the status of my application. If it’s not too much trouble, could you kindly provide me with any updates or feedback you may have? I want to assure you that I remain genuinely interested in the opportunity to join the team at [company] and I would be honored to discuss my qualifications further. If there are any additional materials or information you require from me, please don’t hesitate to let me know. Thank you for your time and consideration. I appreciate the effort you put into recruiting and look forward to hearing from you soon. Warmest regards, (Tap to copy)

🚀 𝗖𝗶𝘀𝗰𝗼 𝗙𝗥𝗘𝗘 𝗧𝗲𝗰𝗵 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 | 𝟱 𝗠𝘂𝘀𝘁-𝗗𝗼 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 🎓 Cisco offers learning opportunities covering some of the most valuable foundations for careers in Cybersecurity, Networking, Linux and IoT. ✅ Beginner-Friendly Tech Skills ✅ Learn In-Demand IT Concepts ✅ Build Practical Knowledge ✅ Strengthen Your Resume ✅ Great for Students & Freshers 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:-  https://pdlink.in/4fhCSKo 🔥 Learn from Cisco • Build Skills • Upgrade Your Resume • Get Career-Ready!

𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 𝘃𝘀. 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝘃𝘀. 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝘃𝘀. 𝗠𝗟 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 Think of them as data detectives. → 𝐅𝐨𝐜𝐮𝐬: Identifying patterns and building predictive models. → 𝐒𝐤𝐢𝐥𝐥𝐬: Machine learning, statistics, Python/R. → 𝐓𝐨𝐨𝐥𝐬: Jupyter Notebooks, TensorFlow, PyTorch. → 𝐆𝐨𝐚𝐥: Extract actionable insights from raw data. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: Creating a recommendation system like Netflix. 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 The architects of data infrastructure. → 𝐅𝐨𝐜𝐮𝐬: Developing data pipelines, storage systems, and infrastructure. → 𝐒𝐤𝐢𝐥𝐥𝐬: SQL, Big Data technologies (Hadoop, Spark), cloud platforms. → 𝐓𝐨𝐨𝐥𝐬: Airflow, Kafka, Snowflake. → 𝐆𝐨𝐚𝐥: Ensure seamless data flow across the organization. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: Designing a pipeline to handle millions of transactions in real-time. 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 Data storytellers. → 𝐅𝐨𝐜𝐮𝐬: Creating visualizations, dashboards, and reports. → 𝐒𝐤𝐢𝐥𝐥𝐬: Excel, Tableau, SQL. → 𝐓𝐨𝐨𝐥𝐬: Power BI, Looker, Google Sheets. → 𝐆𝐨𝐚𝐥: Help businesses make data-driven decisions. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: Analyzing campaign data to optimize marketing strategies. 𝗠𝗟 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 The connectors between data science and software engineering. → 𝐅𝐨𝐜𝐮𝐬: Deploying machine learning models into production. → 𝐒𝐤𝐢𝐥𝐥𝐬: Python, APIs, cloud services (AWS, Azure). → 𝐓𝐨𝐨𝐥𝐬: Kubernetes, Docker, FastAPI. → 𝐆𝐨𝐚𝐥: Make models scalable and ready for real-world applications. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: Deploying a fraud detection model for a bank. 𝗪𝗵𝗮𝘁 𝗣𝗮𝘁𝗵 𝗦𝗵𝗼𝘂𝗹𝗱 𝗬𝗼𝘂 𝗖𝗵𝗼𝗼𝘀𝗲? ☑ Love solving complex problems? → Data Scientist ☑ Enjoy working with systems and Big Data? → Data Engineer ☑ Passionate about visual storytelling? → Data Analyst ☑ Excited to scale AI systems? → ML Engineer Each role is crucial and in demand—choose based on your strengths and career aspirations. What’s your ideal role? Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624 Credits: https://t.me/datasciencefun Like if you need similar content ENJOY LEARNING 👍👍

🚀 𝗔𝗜 & 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲🔥 Learn the most in-demand AI skills from scratch and strengthen your profile with industry-recognized certificates! 🎓 ✅ Beginner-Friendly Courses ✅ Learn Online at Your Own Pace ✅ 100% FREE of cost Perfect for Students, Freshers & Working Professionals looking to build a career in AI/ML. 💼 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:-  https://pdlink.in/4phANS2 📢 Share this with your friends who want to start their AI career!

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✅ SQL Aggregations with Interview Q&A 📊🧮 Aggregation functions help summarize large datasets. Combine them with GROUP BY to analyze grouped data. 1️⃣ COUNT() Returns the number of records.

SELECT COUNT(*) FROM employees;

2️⃣ SUM() Adds up values in a column.

SELECT dept_id, SUM(salary)  
FROM employees  
GROUP BY dept_id;

3️⃣ AVG() Returns the average of values.

SELECT AVG(salary) FROM employees;

4️⃣ MAX() / MIN() Returns the highest/lowest value.

SELECT MAX(salary), MIN(salary) FROM employees;

5️⃣ GROUP BY Groups rows that have the same values in specified columns.

SELECT dept_id, COUNT(*)  
FROM employees  
GROUP BY dept_id;

6️⃣ HAVING Filters groups after aggregation (unlike WHERE which filters rows).

SELECT dept_id, AVG(salary)  
FROM employees  
GROUP BY dept_id  
HAVING AVG(salary) > 50000;

———————— Real-World Interview Questions + Answers Q1: What’s the difference between WHERE and HAVING? A: WHERE filters rows before grouping. HAVING filters after aggregation. Q2: Can you use aggregate functions without GROUP BY? A: Yes. Without GROUP BY, the function applies to the entire table. Q3: How do you find departments with more than 5 employees?

SELECT dept_id, COUNT(*)  
FROM employees  
GROUP BY dept_id  
HAVING COUNT(*) > 5;

Q4: Can you group by multiple columns? A: Yes.

GROUP BY dept_id, job_title

Q5: How do you calculate total and average salary per department?

SELECT dept_id, SUM(salary), AVG(salary)  
FROM employees  
GROUP BY dept_id;

💬 Tap ❤️ for more!

𝗔𝗜 & 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 (𝗡𝗼 𝗖𝗼𝗱𝗶𝗻𝗴 𝗡𝗲𝗲𝗱𝗲𝗱) Apply Now👉:- https://pdlink.in/4aYWald By E&ICT Academy, IIT Roorkee Batch Closing Soon - 18th July 2026

🔟 𝘁𝗶𝗽𝘀 𝗳𝗼𝗿 𝗻𝗲𝘄 𝗰𝗼𝗱𝗲𝗿𝘀: 🔖 1. Learn Fundamentals:  Use W3Schools, FreeCodeCamp, or MDN for solid basics. 2. Watch and Code Along:  Follow YouTube tutorials to code in real-time. 3. Practice Regularly:  Build small projects to sharpen your skills. 4. Join Coding Communities:  Engage on platforms like X, Discord, and Reddit for support. 5. Use AI Tools Wisely: Leverage tools like ChatGPT responsibly to aid learning. 6. Master Git and Version Control:  Learn to manage your code effectively. 7. Stay Updated:  Follow tech blogs, newsletters, and podcasts. 8. Network:  Attend meetups, hackathons, and online coding events. 9. Explore Open Source:  Contribute to projects to gain experience. 10.Never Stop Learning:  Technology evolves—keep exploring new languages and frameworks. Best Programming Resources: https://topmate.io/coding/886839 All the best 👍👍

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Sure! Here’s the revised text with the asterisks replaced by double asterisks: ✅ Coding Interview Acronyms You MUST Know 💻🔥 DSA → Data Structures & Algorithms CPU → Central Processing Unit RAM → Random Access Memory DBMS → Database Management System RDBMS → Relational Database Management System ACID → Atomicity, Consistency, Isolation, Durability OLTP → Online Transaction Processing OLAP → Online Analytical Processing TCP → Transmission Control Protocol IP → Internet Protocol DNS → Domain Name System MVC → Model View Controller MVVM → Model View ViewModel SDLC → Software Development Life Cycle CI/CD → Continuous Integration / Continuous Deployment JWT → JSON Web Token ORM → Object Relational Mapping API → Application Programming Interface REST → Representational State Transfer SOAP → Simple Object Access Protocol Big O → Time & Space Complexity Notation FIFO → First In First Out LIFO → Last In First Out 💬 Double Tap ❤️ for more!

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20 GitHub repos that teach you more than any paid course 1.30-Days-Of-Python — http://github.com/Asabeneh/30-Days-Of-Python Structured 30-day path, beginner to writing real scripts. 2. project-based-learning — http://github.com/practical-tutorials/project-based-learning Huge collection of step-by-step build tutorials across languages. 3. build-your-own-x — http://github.com/codecrafters-io/build-your-own-x Build your own Docker, Redis, git, etc. from scratch. 400k+ stars. 4. ML-For-Beginners — http://github.com/microsoft/ML-For-Beginners Microsoft's free ML course with quizzes & assignments. 5. 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code — http://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 500 project ideas across AI/ML/CV/NLP. 6. freeCodeCamp — http://github.com/freeCodeCamp/freeCodeCamp Full curriculum: web dev, JS algorithms, data science, more. 7. developer-roadmap— http://github.com/kamranahmedse/developer-roadmap Visual roadmaps for every dev role — frontend, backend, DevOps. 8. coding-interview-university — http://github.com/jwasham/coding-interview-university Full CS study plan to prep for software engineering interviews. 9. system-design-primer — http://github.com/donnemartin/system-design-primer Learn how to design large-scale systems, with real examples. 10. javascript-algorithms — http://github.com/trekhleb/javascript-algorithms Algorithms & data structures explained and implemented in JS. 11. You-Dont-Know-JS — http://github.com/getify/You-Dont-Know-JS Deep-dive book series on how JavaScript actually works. 12. clean-code-javascript — http://github.com/ryanmcdermott/clean-code-javascript Clean code principles adapted for JS with real examples. 13. public-apis — http://github.com/public-apis/public-apis Free APIs for literally any project idea you have. 14. free-programming-books — http://github.com/EbookFoundation/free-programming-books Massive list of free books across every language and stack. 15. ossu/computer-science — http://github.com/ossu/computer-science Full free CS degree curriculum, self-paced. 16. app-ideas — http://github.com/florinpop17/app-ideas Curated project ideas with difficulty levels to build a portfolio. 17. awesome-python — http://github.com/vinta/awesome-python Every notable Python framework, library, and resource in one place. 18. awesome-machine-learning — http://github.com/josephmisiti/awesome-machine-learning Curated ML frameworks and resources by language. 19. tech-interview-handbook — http://github.com/yangshun/tech-interview-handbook Curated interview prep material used by real candidates who got hired. 20. awesome — http://github.com/sindresorhus/awesome The meta-list. Every "awesome" list for every topic that exists. Do not forget to React ❤️ to this message for more content like this 👇 Thanks for joining all 💙🙏