Coding Interview Resources

Free Resources To Crack Coding Interviews 👇👇 Coding Interview Prep FREE CERTIFIED COURSE https://www.freecodecamp.org/learn/coding-interview-prep/#take-home-projects Python Interview Questions and Answers https://t.me/dsabooks/75 Beginner's guide for DSA https://www.geeksforgeeks.org/the-ultimate-beginners-guide-for-dsa/amp/ Cracking the coding interview FREE BOOK https://www.pdfdrive.com/cracking-the-coding-interview-189-programming-questions-and-solutions-d175292720.html DSA Interview Questions and Answers https://t.me/crackingthecodinginterview/77 Cracking the Coding interview: Learn 5 Essential Patterns [4.5 star ratings out of 5] https://bit.ly/3GUBk56 Data Science Interview Questions and Answers https://t.me/datasciencefun/958 Java Interview Questions with Answers https://t.me/Curiousprogrammer/106 ENJOY LEARNING 👍👍

List of most asked Programming Interview Questions. Are you preparing for a coding interview? This tweet is for you. It contains a list of the most asked interview questions from each topic. Arrays - How is an array sorted using quicksort? - How do you reverse an array? - How do you remove duplicates from an array? - How do you find the 2nd largest number in an unsorted integer array? Linked Lists - How do you find the length of a linked list? - How do you reverse a linked list? - How do you find the third node from the end? - How are duplicate nodes removed in an unsorted linked list? Strings - How do you check if a string contains only digits? - How can a given string be reversed? - How do you find the first non-repeated character? - How do you find duplicate characters in strings? Binary Trees - How are all leaves of a binary tree printed? - How do you check if a tree is a binary search tree? - How is a binary search tree implemented? - Find the lowest common ancestor in a binary tree? Graph - How to detect a cycle in a directed graph? - How to detect a cycle in an undirected graph? - Find the total number of strongly connected components? - Find whether a path exists between two nodes of a graph? - Find the minimum number of swaps required to sort an array. Dynamic Programming 1. Find the longest common subsequence? 2. Find the longest common substring? 3. Coin change problem? 4. Box stacking problem? 5. Count the number of ways to cover a distance? Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Here's a short roadmap to crack an IT job with a non-CS background 🚀 1. 📚 Learn basics of CS and programming. 2. 🎯 Choose a specialization (e.g., web dev, data analysis). 3. 🏆 Complete online courses and certifications. 4. 🛠️ Build a portfolio of projects. 5. 🤝 Network with professionals. 6. 💼 Seek internships for experience. 7. 📚 Keep learning and stay updated. 8. 🧠 Develop soft skills. 9. 📝 Prepare for interviews. 10. 💪 Stay persistent and positive! Good luck!

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 👍👍

⭕ TECH MAHINDRA Interview Exp ⭕ 1) Self Intro. 2) Project. 3) Qns on Project. 4) Which Programming Language      you r Familiar with It. 5) What is Primarykey, Foreignkey. 6) Views in SQL. 7) Syntax of View. 8) Rank. 9) External Table. 10) Method Overloading. 11) Method Overriding. 12) Inheritance. 13) Explain Types of Inheritance 14) Why Multiple Inheritance is not        Supported. 15) Is Multiple Inheritance.       Supported injava and wha is it. 16) Relocation. 17) Night Shifts. 18) Why you Choose TechM. 19) About TechM.

Leetcode is a tool to learn Neetcode is a tool to learn CodeChef is a tool to learn Codeforces is a tool to learn HackerRank is a tool to learn GeeksForGeeks is a tool to learn It doesn't matter: - which platform you are using - or how many problems you solve All that matters is how strong you grasp concepts and adapt to problems. Don't chase the status of 500 or 1000 problems solved. Chase proper learning & training your mind for problem-solving. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

International students are having a tough time securing a full time job in Tech. Reasons 1. Market has limited opportunities for entry level junior data/software engineers. 2. People having 0-3 years of workex are competing against job seekers having 8+ years of seasoned experience. 3. Lot of companies have their operations in off-shore, as companies grow the headcount of offshore>>onshore. Solution : Build up relevant skillsets, latch on to the newer technologies that will bring you at par with experienced candidates. Build apps/ai models/data pipelines/dashboards that tracks live data. People who have secured job has everything to lose and their routine is restricted and have limitied time to be dedicated to learning. You on the other hand have nothing to lose and everything to gain. Request for that coffee chat. Take that certification exam. Attend that quarterly event. Success is sweeter when its delayed.

5 Sites to Prepare for Tech Interviews: 1. Leetcode 🔗 leetcode.com 2. Interviewing .io 🔗 interviewing.io 3. Coding Interview University 🔗 https://github.com/jwasham/coding-interview-university 4. JavaScript Algorithms 🔗 https://github.com/trekhleb/javascript-algorithms 5. JavaScript Questions 🔗 https://github.com/lydiahallie/javascript-questions ➡️ Give Reactions 🤟

Preparing for a Java developer interview can be a bit overwhelming, but breaking it down by difficulty and experience level can make it more manageable. Whether you're a fresher or an experienced developer, here's a guide to help you focus your preparation and walk into your interview with confidence. 𝗙𝗼𝗿 𝗔𝗹𝗹 𝗟𝗲𝘃𝗲𝗹𝘀 (𝗜𝗻𝗰𝗹𝘂𝗱𝗶𝗻𝗴 𝗙𝗿𝗲𝘀𝗵𝗲𝗿𝘀) ➤ Topic 1: Project Flow and Architecture (Medium) - These questions are designed to gauge your understanding of project development, teamwork, and problem-solving. Be ready to discuss a project you've worked on, including the tech stack used, the challenges you faced, and how you overcame them. 𝗙𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗖𝗼𝗿𝗲 𝗝𝗮𝘃𝗮 𝗦𝗸𝗶𝗹𝗹𝘀 (𝟭-𝟯 𝗬𝗲𝗮𝗿𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲) ➤ Topic 2: Core Java (Medium to Hard) - Fundamental Java concepts. You'll likely face questions on strings, object-oriented programming (OOP), collections, exception handling, and multithreading. 𝗙𝗼𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 (𝟯+ 𝗬𝗲𝗮𝗿𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲) ➤ Topic 3: Java 8/11/17 Features (Hard) - This is where the interview gets more challenging. You'll asked advanced features introduced in recent Java versions, such as lambda expressions, functional interfaces, the Stream API, and modules. ➤ Topic 4: Spring Framework, Spring Boot, Microservices, and REST API (Hard) - Expect questions on popular frameworks and backend development architectures. Be prepared to explain concepts like dependency injection, Spring MVC, and microservices. 𝗙𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 ➤ Topic 5: Hibernate/Spring Data JPA/Database (Hard) - This section focuses on data persistence with JPA and working with relational (SQL) or NoSQL databases. Be ready to discuss JPA repositories, entity relationships, and complex querying techniques. 𝗙𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗔𝗱𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝗸𝗶𝗹𝗹𝘀 ➤ Topic 6: Coding (Medium to Hard) - You'll likely encounter coding challenges related to data structures and algorithms (DSA), as well as using the Java Stream API. ➤ Topic 7: DevOps Questions on Deployment Tools (Advanced) - These questions are often posed by managers or leads, especially if you're applying for a role that involves DevOps. Be prepared to discuss deployment tools like Jenkins, Kubernetes, and cloud platforms. ➤ Topic 8: Best Practices (Medium) - Interviewers may ask about design patterns like Singletons, Factories, or Observers to see how well you write clean, reusable code. All the best 👍👍

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 Credits: https://t.me/free4unow_backup All the best 👍👍

Three-Tier Architecture __ _ Three-tier architecture is a software design pattern that separates an application into three layers: presentation, business logic, and data. This separation promotes scalability, maintainability, and flexibility. 1️⃣Presentation Layer (Client Tier)    - Role: Manages the user interface.    - Components: Web browsers, mobile apps.    - Technologies: HTML, CSS, JavaScript.    2️⃣Business Logic Layer (Application Tier)    - Role: Processes business logic and rules.    - Components: Application servers.    - Technologies: Java, .NET, Python.    3️⃣Data Layer (Data Tier)    - Role: Manages data storage and retrieval.    - Components: Database servers.    - Technologies: SQL, NoSQL databases.

How to guess the solution for DSA problems? Yes, it is possible. You can predict the solution for a problem by analyzing the constraints. Curious if you need a greedy approach or a backtracking solution? Trying to decide between an O(n^3) or an O(n log n) approach? Just scroll down the LeetCode question and look at the constraints of the main element. Wondering if you should use dynamic programming or plain recursion? Should your solution be O(n^2) or O(n)? Simply examine the constraints of the main variable. Here's a quick guide based on the value of (n): - If n <= 12 Time complexity can be O(n!). - If n <= 25 Time complexity can be O(2^n). - If n <= 100 Time complexity can be O(n^4). - If n <= 500 Time complexity can be O(n^3). - If n <= 10 ^ 4 Time complexity can be O(n^2). - If n <= 10 ^ 6 Time complexity can be O(n log n). - If n <= 10 ^ 8 Time complexity can be O(n). - If n > 10 ^ 8 Time complexity can be O(log n) or 0(1). - If n <= 10 ^ 9 Time complexity can be O(sqrt{n}). - If n > 10 ^ 9 Time complexity can be O(log n) or 0(1). Understanding these constraints can help you choose the right algorithm and improve your problem-solving efficiency. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Beginner’s Roadmap to Learn Data Structures & Algorithms 1. Foundations: Start with the basics of programming and mathematical concepts to build a strong foundation. 2. Data Structure: Dive into essential data structures like arrays, linked lists, stacks, and queues to organise and store data efficiently. 3. Searching & Sorting: Learn various search and sort techniques to optimise data retrieval and organisation. 4. Trees & Graphs: Understand the concepts of binary trees and graph representation to tackle complex hierarchical data. 5. Recursion: Grasp the principles of recursion and how to implement recursive algorithms for problem-solving. 6. Advanced Data Structures: Explore advanced structures like hashing, heaps, and hash maps to enhance data manipulation. 7. Algorithms: Master algorithms such as greedy, divide and conquer, and dynamic programming to solve intricate problems. 8. Advanced Topics: Delve into backtracking, string algorithms, and bit manipulation for a deeper understanding. 9. Problem Solving: Practice on coding platforms like LeetCode to sharpen your skills and solve real-world algorithmic challenges. 10. Projects & Portfolio: Build real-world projects and showcase your skills on GitHub to create an impressive portfolio. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

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Here are the top 16 OOP interview questions👇 1. What is the difference between a class and an object? 2. What is the difference between a static and non-static method? 3. What is the purpose of an interface in OOP? 4. Explain the 4 pillars of OOP. 5. What is the difference between a public and private constructor? 6. What is the difference between an abstract class and an interface? 7. What is the difference between a shallow copy and a deep copy? 8. What is the role of the "this" keyword in OOP? 9. What is a virtual function, and how is it implemented in OOP? 10. What is the difference between overloading and overriding a method? 11. What is an Abstract class? 12. Explain different types of constructors. 13. What is Coupling in OOP and why is it helpful? 14. What is a destructor in OOP? 15. What is a static keyword in cpp? 16. What is the difference between encapsulation and data abstraction? Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍