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Coding & AI Resources

Coding & AI Resources

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📚Get daily updates for : ✅ Free resources ✅ All Free notes ✅ Internship,Jobs and a lot more....😍 📍Join & Share this channel with your friends and college mates ❤️ Managed by: @love_data Buy ads: https://telega.io/c/leadcoding

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📈 Análisis del canal de Telegram Coding & AI Resources

El canal Coding & AI Resources (@leadcoding) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 35 263 suscriptores, ocupando la posición 5 393 en la categoría Educación y el puesto 10 892 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 35 263 suscriptores.

Según los últimos datos del 31 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -134, y en las últimas 24 horas de -4, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.41%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.75% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 850 visualizaciones. En el primer día suele acumular 266 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
  • Intereses temáticos: El contenido se centra en temas clave como learning, link:-, element, programming, analytic.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“📚Get daily updates for : ✅ Free resources ✅ All Free notes ✅ Internship,Jobs and a lot more....😍 📍Join & Share this channel with your friends and college mates ❤️ Managed by: @love_data Buy ads: https://telega.io/c/leadcoding”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 01 noviembre, 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 Educación.

35 263
Suscriptores
-424 horas
-387 días
-13430 días
Archivo de publicaciones
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 👍👍

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API Reference.pdf12.58 MB

30-day roadmap to learn Python up to an intermediate level Week 1: Python Basics *Day 1-2:* - Learn about Python, its syntax, and how to install Python on your computer. - Write your first "Hello, World!" program. - Understand variables and data types (integers, floats, strings). *Day 3-4:* - Explore basic operations (arithmetic, string concatenation). - Learn about user input and how to use the input() function. - Practice creating and using variables. *Day 5-7:* - Dive into control flow with if statements, else statements, and loops (for and while). - Work on simple programs that involve conditions and loops. Week 2: Functions and Modules *Day 8-9:* - Study functions and how to define your own functions using def. - Learn about function arguments and return values. *Day 10-12:* - Explore built-in functions and libraries (e.g., len(), random, math). - Understand how to import modules and use their functions. *Day 13-14:* - Practice writing functions for common tasks. - Create a small project that utilizes functions and modules. Week 3: Data Structures *Day 15-17:* - Learn about lists and their operations (slicing, appending, removing). - Understand how to work with lists of different data types. *Day 18-19:* - Study dictionaries and their key-value pairs. - Practice manipulating dictionary data. *Day 20-21:* - Explore tuples and sets. - Understand when and how to use each data structure. Week 4: Intermediate Topics *Day 22-23:* - Study file handling and how to read/write files in Python. - Work on projects involving file operations. *Day 24-26:* - Learn about exceptions and error handling. - Explore object-oriented programming (classes and objects). *Day 27-28:* - Dive into more advanced topics like list comprehensions and generators. - Study Python's built-in libraries for web development (e.g., requests). *Day 29-30:* - Explore additional libraries and frameworks relevant to your interests (e.g., NumPy for data analysis, Flask for web development, or Pygame for game development). - Work on a more complex project that combines your knowledge from the past weeks. Throughout the 30 days, practice coding daily, and don't hesitate to explore Python's documentation and online resources for additional help. Learning Python is a dynamic process, so adapt the roadmap based on your progress and interests. Good luck with your Python journey!

🖥 Top Programming Languages to learn in 2024 - [Part 2] 🖥 6. Go PRogramming - go.dev - learn-golang.org 7. Kotlin - kotlinlang.org - t.me/codingwithsagar/327 8. Python - learnpython.org - t.me/pythonanalyst 9. SQL - learnsql.com - t.me/sqlanalyst 10. R Programming - w3schools.com/r/ - r-coder.com

🖥 Top Programming Languages to learn in 2024 - [Part 1] 🖥 1. JavaScript - learnjavascript.online - t.me/javascript_courses/4 - learn-js.org 2. Java - learnjavaonline.org - javatpoint.com 3. C# - learncs.org - w3schools.com 4. TypeScript - Typescriptlang.org - learntypescript.dev 5. Rust - rust-lang.org - t.me/Curiousprogrammer/376 - exercism.org

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Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch Автор: Maxime Labonne

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