Coding Interview Resources

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Best Programming Languages for Hacking: 1. Python It’s no surprise that Python tops our list. Referred to as the defacto hacking programing language, Python has indeed played a significant role in the writing of hacking scripts, exploits, and malicious programs. 2. C C is critical language in the Hacking community. Most of the popular operating systems we have today run on a foundation of C language. C is an excellent resource in reverse engineering of software and applications. These enable hackers to understand the working of a system or an app. 3. Javascript For quite some time, Javascript(JS) was a client-side scripting language. With the release of Node.js, Javascript now supports backend development. To hackers, this means a broader field of exploitation. 4. PHP For a long time now, PHP has dominated the backend of most websites and web applications. If you are into web hacking, then getting your hands on PHP would be of great advantage. 5. C++ Have you ever thought of cracking corporate(paid) software? Here is your answer. The hacker community has significantly implemented C++ programming language to remove trial periods on paid software and even the operating system. 6. SQL SQL – Standard Query Language. It is a programming language used to organize, add, retrieve, remove, or edit data in a database. A lot of systems store their data in databases such as MySQL, MS SQL, and PostgreSQL. Using SQL, hackers can perform an attack known as SQL injection, which will enable them to access confidential information. 7. Java Despite what many may say, a lot of backdoor exploits in systems are written in Java. It has also been used by hackers to perform identity thefts, create botnets, and even perform malicious activities on the client system undetected.

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DSA (Data Structures and Algorithms) Essential Topics for Interviews 1️⃣ Arrays and Strings Basic operations (insert, delete, update) Two-pointer technique Sliding window Prefix sum Kadane’s algorithm Subarray problems 2️⃣ Linked List Singly & Doubly Linked List Reverse a linked list Detect loop (Floyd’s Cycle) Merge two sorted lists Intersection of linked lists 3️⃣ Stack & Queue Stack using array or linked list Queue and Circular Queue Monotonic Stack/Queue LRU Cache (LinkedHashMap/Deque) Infix to Postfix conversion 4️⃣ Hashing HashMap, HashSet Frequency counting Two Sum problem Group Anagrams Longest Consecutive Sequence 5️⃣ Recursion & Backtracking Base cases and recursive calls Subsets, permutations N-Queens problem Sudoku solver Word search 6️⃣ Trees & Binary Trees Traversals (Inorder, Preorder, Postorder) Height and Diameter Balanced Binary Tree Lowest Common Ancestor (LCA) Serialize & Deserialize Tree 7️⃣ Binary Search Trees (BST) Search, Insert, Delete Validate BST Kth smallest/largest element Convert BST to DLL 8️⃣ Heaps & Priority Queues Min Heap / Max Heap Heapify Top K elements Merge K sorted lists Median in a stream 9️⃣ Graphs Representations (adjacency list/matrix) DFS, BFS Cycle detection (directed & undirected) Topological Sort Dijkstra’s & Bellman-Ford algorithm Union-Find (Disjoint Set) 10️⃣ Dynamic Programming (DP) 0/1 Knapsack Longest Common Subsequence Matrix Chain Multiplication DP on subsequences Memoization vs Tabulation 11️⃣ Greedy Algorithms Activity selection Huffman coding Fractional knapsack Job scheduling 12️⃣ Tries Insert and search a word Word search Auto-complete feature 13️⃣ Bit Manipulation XOR, AND, OR basics Check if power of 2 Single Number problem Count set bits Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X ENJOY LEARNING 👍👍

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You will not learn system design in a month. You will not master DSA in a month. You will not suddenly understand how to solve problems at scale in a month. You won’t grasp scalability, databases, and caching overnight. And you most definitely won’t internalize every distributed system pattern just by reading a few blogs. Because software engineering is an ocean: deep, vast, and ever-expanding. And you can’t cross an ocean in a single leap. In a month, you’ll realize you’re only scratching the surface. You’ll see more gaps than answers. You’ll feel like there’s too much to learn and too little time. But that’s where most people give up. That’s where frustration makes them quit. Don’t be one of them. Take it one step at a time. Real expertise doesn’t come from rushing. It comes from consistent, deliberate learning over years. It comes from revisiting the same concepts and seeing them from new perspectives each time. So trust your own pace. Stay in the game long enough to connect the dots. And one day, the same concepts that once seemed impossible will feel like second nature. Just keep collecting buckets.

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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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5 Algorithms you must know as a data scientist 👩‍💻 🧑‍💻 1. Dimensionality Reduction - PCA, t-SNE, LDA 2. Regression models - Linesr regression, Kernel-based regression models, Lasso Regression, Ridge regression, Elastic-net regression 3. Classification models - Binary classification- Logistic regression, SVM - Multiclass classification- One versus one, one versus many - Multilabel classification 4. Clustering models - K Means clustering, Hierarchical clustering, DBSCAN, BIRCH models 5. Decision tree based models - CART model, ensemble models(XGBoost, LightGBM, CatBoost) Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624 Join our WhatsApp channel: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D Like if you need similar content 😄👍

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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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### Learn Git Easily 🤩 Here's all you need to get started 🙌 1. Introduction to Git - What is Git? - Differences between Git and other version control systems - Installing Git 2. Git Basics - Creating a new repository - Cloning a repository - Understanding the working directory, staging area, and repository 3. Basic Commands - git init - git clone - git add - git commit - git status - git log 4. Branching and Merging - Understanding branches - Creating branches (git branch) - Switching branches (git checkout) - Merging branches (git merge) - Resolving merge conflicts 5. Remote Repositories - Adding a remote repository (git remote add) - Fetching changes (git fetch) - Pushing changes (git push) - Pulling changes (git pull) 6. Stashing Changes - Stashing modifications (git stash) - Applying stashed changes (git stash apply) - Listing and dropping stashes 7. Viewing Changes - Checking differences (git diff) - Viewing commit history (git log) - Viewing specific changes in a commit (git show) 8. Reverting Changes - Undoing changes (git checkout) - Reverting commits (git revert) - Resetting commits (git reset) 9. Working with Tags - Creating tags (git tag) - Listing tags - Pushing tags to remote 10. Collaboration and Workflows - Pull Requests (PRs) in platforms like GitHub and GitLab - Forking repositories - Code reviews and merging PRs 11. Git Configurations - Setting up user information (git config) - Global vs. local configurations - Configuring SSH keys for GitHub 12. Best Practices - Writing good commit messages - Branching strategies (e.g., Git Flow) - Keeping a clean commit history 13. Git Hooks - Introduction to Git hooks - Common hooks (pre-commit, post-commit) 14. Advanced Git Commands - Cherry-picking commits (git cherry-pick) - Interactive rebasing (git rebase -i) - Squashing commits 15. Using GUI Tools - Overview of popular Git GUI clients (e.g., SourceTree, GitKraken) 16. Git Troubleshooting - Common issues and how to resolve them - Understanding the .git directory 17. Resources for Continued Learning - Official Git documentation - Online tutorials and courses - Git cheat sheets

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