Coding Interview Resources

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 💙🙏

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Cheat sheet on Python Frameworks: Django: A full-featured web framework with built-in ORM, admin panel, and security features. Flask: A lightweight microframework with a minimal set of features and high flexibility. ORM & Admin: Built-in to Django, but need to be connected separately in Flask. Security: Django has built-in security mechanisms, while in Flask, they need to be configured manually. Testing: Django offers built-in testing tools, while Flask relies on third-party libraries. Use Cases: Django is suitable for large and complex projects, while Flask is better for small applications, APIs, and prototypes.

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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://whatsapp.com/channel/0029VamdH5mHAdNMHMSBwg1s Like for more ❤️

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🧠 SQL Interview Question (Commonly Asked) 📌 products(product_id, product_name, category_id, price) ❓ Ques : 👉 Find the second highest priced product in each category. 🧩 How Interviewers Expect You to Think • Partition data by category • Rank products based on price (descending) • Understand difference between RANK, DENSE_RANK, and ROW_NUMBER • Handle ties properly • Filter after ranking logic 💡 SQL Solution WITH ranked_products AS ( SELECT product_id, product_name, category_id, price, DENSE_RANK() OVER ( PARTITION BY category_id ORDER BY price DESC ) AS price_rank FROM products ) SELECT product_id, product_name, category_id, price FROM ranked_products WHERE price_rank = 2; 🔥 Why this question is powerful: • Tests window functions deeply • Checks ranking logic understanding • Very common in Data Analyst interviews ❤️ React if you want more scenario-based SQL questions

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Master Javascript : The JavaScript Tree 👇 | |── Variables | ├── var | ├── let | └── const | |── Data Types | ├── String | ├── Number | ├── Boolean | ├── Object | ├── Array | ├── Null | └── Undefined | |── Operators | ├── Arithmetic | ├── Assignment | ├── Comparison | ├── Logical | ├── Unary | └── Ternary (Conditional) ||── Control Flow | ├── if statement | ├── else statement | ├── else if statement | ├── switch statement | ├── for loop | ├── while loop | └── do-while loop | |── Functions | ├── Function declaration | ├── Function expression | ├── Arrow function | └── IIFE (Immediately Invoked Function Expression) | |── Scope | ├── Global scope | ├── Local scope | ├── Block scope | └── Lexical scope ||── Arrays | ├── Array methods | | ├── push() | | ├── pop() | | ├── shift() | | ├── unshift() | | ├── splice() | | ├── slice() | | └── concat() | └── Array iteration | ├── forEach() | ├── map() | ├── filter() | └── reduce()| |── Objects | ├── Object properties | | ├── Dot notation | | └── Bracket notation | ├── Object methods | | ├── Object.keys() | | ├── Object.values() | | └── Object.entries() | └── Object destructuring ||── Promises | ├── Promise states | | ├── Pending | | ├── Fulfilled | | └── Rejected | ├── Promise methods | | ├── then() | | ├── catch() | | └── finally() | └── Promise.all() | |── Asynchronous JavaScript | ├── Callbacks | ├── Promises | └── Async/Await | |── Error Handling | ├── try...catch statement | └── throw statement | |── JSON (JavaScript Object Notation) ||── Modules | ├── import | └── export | |── DOM Manipulation | ├── Selecting elements | ├── Modifying elements | └── Creating elements | |── Events | ├── Event listeners | ├── Event propagation | └── Event delegation | |── AJAX (Asynchronous JavaScript and XML) | |── Fetch API ||── ES6+ Features | ├── Template literals | ├── Destructuring assignment | ├── Spread/rest operator | ├── Arrow functions | ├── Classes | ├── let and const | ├── Default parameters | ├── Modules | └── Promises | |── Web APIs | ├── Local Storage | ├── Session Storage | └── Web Storage API | |── Libraries and Frameworks | ├── React | ├── Angular | └── Vue.js ||── Debugging | ├── Console.log() | ├── Breakpoints | └── DevTools | |── Others | ├── Closures | ├── Callbacks | ├── Prototypes | ├── this keyword | ├── Hoisting | └── Strict mode | | END __

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✅ Data Science: Tools You Should Know as a Beginner 🧰📊 Mastering these tools helps you build real-world data projects faster and smarter: 1️⃣ Python ✔ Most popular language in data science ✔ Libraries: NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn 📌 Use: Data cleaning, EDA, modeling, automation 2️⃣ Jupyter Notebook ✔ Interactive coding environment ✔ Great for documentation + visualization 📌 Use: Prototyping & explaining models 3️⃣ SQL ✔ Essential for querying databases 📌 Use: Data extraction, filtering, joins, aggregations 4️⃣ Excel / Google Sheets ✔ Quick analysis & reports 📌 Use: Data exploration, pivot tables, charts 5️⃣ Power BI / Tableau ✔ Drag-and-drop dashboards 📌 Use: Visual storytelling & business insights 6️⃣ Git & GitHub ✔ Track code changes + collaborate 📌 Use: Version control, building your portfolio 7️⃣ Scikit-learn ✔ Ready-to-use ML models 📌 Use: Classification, regression, model evaluation 8️⃣ Google Colab / Kaggle Notebooks ✔ Free, cloud-based Python environment 📌 Use: Practice & run notebooks without setup 🧠 Bonus: • VS Code – for scalable Python projects • APIs – for real-world data access • Streamlit – build data apps without frontend knowledge Double Tap ♥️ For More

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7. Layers in a Software Application A well-designed application is divided into layers. Presentation Layer  • User Interface  • Displays information  • Accepts user input  Business Logic Layer  • Processes data  • Applies business rules  • Validates requests  Data Layer  • Stores information  • Retrieves data  • Communicates with databases  Separating these layers makes applications easier to maintain. 8. Design Principles Professional developers follow design principles to write maintainable software. Some important principles include:  • Keep code simple  • Avoid repeating code DRY  • Separate responsibilities  • Write reusable components  • Prefer readability over complexity  These principles make projects easier to understand and extend. 9. System Design Basics System Design focuses on building applications that can handle growth. Questions to consider:  • How will the application handle thousands of users?  • How can performance be improved?  • How can downtime be minimized?  • How should data be stored?  Learning system design helps you think beyond writing code. 10. Scalability Scalability means an application can handle increasing users without major performance issues. Example: 100 Users ✅ 10,000 Users ✅ 1 Million Users ✅  A scalable architecture ensures the application continues to perform well as demand grows. 11. Security in Architecture Security should be part of the architecture from the beginning. Consider:  • Authentication  • Authorization  • Data Encryption  • Secure APIs  • Input Validation  Ignoring security can expose applications to serious risks. Common Architecture Tools Professional teams often use:  • Docker  • Kubernetes  • API Gateways  • Message Queues  • Load Balancers  These tools help build reliable and scalable systems. Common Beginner Mistakes  • Building everything in one file  • Mixing frontend and backend logic  • Ignoring project structure  • Creating tightly coupled code  • Not separating responsibilities  Good architecture prevents these problems. How to Learn Software Architecture Follow this learning path: Learn Monolithic Architecture → Understand REST APIs → Build Small Applications → Learn Layered Architecture → Explore Microservices → Study System Design  Take one step at a time. Why This Step is Important Understanding software architecture helps you:  • Build scalable applications  • Write maintainable code  • Work effectively in development teams  • Understand enterprise software  • Prepare for software engineering interviews  Final Advice Great developers don't just write code. They design software that is easy to maintain, secure, and scalable.  Good Architecture → Better Code → Better Software → Better User Experience  Double Tap ❤️ For More