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📈 Análisis del canal de Telegram Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books

El canal Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 56 114 suscriptores, ocupando la posición 2 374 en la categoría Tecnologías y Aplicaciones y el puesto 6 527 en la región India.

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Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 56 114 suscriptores.

Según los últimos datos del 10 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 89, y en las últimas 24 horas de 1, conservando un alto alcance.

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  • Alcance de las publicaciones: Cada publicación recibe en promedio 1 485 visualizaciones. En el primer día suele acumular 488 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 4.
  • Intereses temáticos: El contenido se centra en temas clave como algorithm, structure, stack, javascript, programming.

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Everything about programming for beginners * Python programming * Java programming * App development * Machine Learning * Data Science Managed by: @love_data

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 11 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

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Let's explore some of the best open source projects by language. 1⃣ Best Python Open Source Projects 🚣‍♂ TensorFlow 🚣‍♂ Mat
Let's explore some of the best open source projects by language. 1⃣ Best Python Open Source Projects 🚣‍♂ TensorFlow 🚣‍♂ Matplotlib 🚣‍♂ Flask 🚣‍♂ Django 🚣‍♂ PyTorch 2⃣ Best JavaScript Open Source Projects 🚣‍♂ React 🚣‍♂ Node.JS 🚣‍♂ jQuery 3⃣ Best C++ Open Source Projects 🚣‍♂ Serenity 🚣‍♂ MongoDB 🚣‍♂ SonarSource 🚣‍♂ OBS Studio 🚣‍♂ Electron 4⃣ Best Java Open Source Projects 🚣‍♂ Mockito 🚣‍♂ Realm 🚣‍♂ Jenkins 🚣‍♂ Guava 🚣‍♂ Moshi It's time to start developing your own open source projects. Explore the projects

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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 You can check these resources for Coding interview Preparation Credits: https://t.me/free4unow_backup All the best 👍👍

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🏟 Here is a complete roadmap to learn Data Structures and Algorithms (DSA) 🏟 1. Basics of Programming: Start by learning the basics of a programming language like Python, Java, or C++. Understand concepts like variables, loops, functions, and arrays. 2. Data Structures: Study fundamental data structures like arrays, linked lists, stacks, queues, trees, graphs, and hash tables. Understand the operations that can be performed on these data structures and their time complexities. 3. Algorithms: Learn common algorithms like searching, sorting, recursion, dynamic programming, greedy algorithms, and divide and conquer. Understand how these algorithms work and their time complexities. 4. Problem Solving: Practice solving coding problems on platforms like LeetCode, HackerRank, or Codeforces. Start with easy problems and gradually move to medium and hard problems. 5. Complexity Analysis: Learn how to analyze the time and space complexity of algorithms. Understand Big O notation and how to calculate the complexity of different algorithms. 6. Advanced Data Structures: Study advanced data structures like AVL trees, B-trees, tries, segment trees, and fenwick trees. Understand when and how to use these data structures in problem-solving. 7. Graph Algorithms: Learn graph traversal algorithms like BFS and DFS. Study algorithms like Dijkstra's algorithm, Bellman-Ford algorithm, and Floyd-Warshall algorithm for shortest path problems. 8. Dynamic Programming: Master dynamic programming techniques for solving complex problems efficiently. Practice solving dynamic programming problems to build your skills. 9. Practice and Review: Regularly practice coding problems and review your solutions. Analyze your mistakes and learn from them to improve your problem-solving skills. 10. Mock Interviews: Prepare for technical interviews by participating in mock interviews and solving interview-style coding problems. Practice explaining your thought process and reasoning behind your solutions. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

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9 tips to learn Data Structures & Algorithms (DSA) effectively: Master one language first (like Python, Java, or C++) Start with basics: arrays, strings, linked lists Practice consistently on coding platforms Visualize problems to understand them better Learn patterns — sliding window, two pointers, recursion Understand time and space complexity Solve problems before reading solutions Revisit and revise tough problems Build a strong foundation before diving into advanced topics Coding Interview Resources:👇 https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X ENJOY LEARNING 👍👍

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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 __

Repost from Generative AI
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Don't overwhelm to learn JavaScript, JavaScript is only this much 1.Variables • var • let • const 2. Data Types • number • string • boolean • null • undefined • symbol 3.Declaring variables • var • let • const 4.Expressions Primary expressions • this • Literals • [] • {} • function • class • function* • async function • async function* • /ab+c/i • string • ( ) Left-hand-side expressions • Property accessors • ?. • new • new .target • import.meta • super • import() 5.operators • Arithmetic Operators: +, -, *, /, % • Comparison Operators: ==, ===, !=, !==, <, >, <=, >= • Logical Operators: &&, ||, ! 6.Control Structures • if • else if • else • switch • case • default 7.Iterations/Loop • do...while • for • for...in • for...of • for await...of • while 8.Functions • Arrow Functions • Default parameters • Rest parameters • arguments • Method definitions • getter • setter 9.Objects and Arrays • Object Literal: { key: value } • Array Literal: [element1, element2, ...] • Object Methods and Properties • Array Methods: push(), pop(), shift(), unshift(), splice(), slice(), forEach(), map(), filter() 10.Classes and Prototypes • Class Declaration • Constructor Functions • Prototypal Inheritance • extends keyword • super keyword • Private class features • Public class fields • static • Static initialization blocks 11.Error Handling • try, • catch, • finally (exception handling) ADVANCED CONCEPTS 12.Closures • Lexical Scope • Function Scope • Closure Use Cases 13.Asynchronous JavaScript • Callback Functions • Promises • async/await Syntax • Fetch API • XMLHttpRequest 14.Modules • import and export Statements (ES6 Modules) • CommonJS Modules (require, module.exports) 15.Event Handling • Event Listeners • Event Object • Bubbling and Capturing 16.DOM Manipulation • Selecting DOM Elements • Modifying Element Properties • Creating and Appending Elements 17.Regular Expressions • Pattern Matching • RegExp Methods: test(), exec(), match(), replace() 18.Browser APIs • localStorage and sessionStorage • navigator Object • Geolocation API • Canvas API 19.Web APIs • setTimeout(), setInterval() • XMLHttpRequest • Fetch API • WebSockets 20.Functional Programming • Higher-Order Functions • map(), reduce(), filter() • Pure Functions and Immutability 21.Promises and Asynchronous Patterns • Promise Chaining • Error Handling with Promises • Async/Await 22.ES6+ Features • Template Literals • Destructuring Assignment • Rest and Spread Operators • Arrow Functions • Classes and Inheritance • Default Parameters • let, const Block Scoping 23.Browser Object Model (BOM) • window Object • history Object • location Object • navigator Object 24.Node.js Specific Concepts • require() • Node.js Modules (module.exports) • File System Module (fs) • npm (Node Package Manager) 25.Testing Frameworks • Jasmine • Mocha • Jest

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