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Coding Interview Resources

Coding Interview Resources

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This channel contains the free resources and solution of coding problems which are usually asked in the interviews. Managed by: @love_data

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📈 Análisis del canal de Telegram Coding Interview Resources

El canal Coding Interview Resources (@crackingthecodinginterview) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 52 139 suscriptores, ocupando la posición 2 571 en la categoría Tecnologías y Aplicaciones y el puesto 7 217 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 52 139 suscriptores.

Según los últimos datos del 11 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 148, y en las últimas 24 horas de 5, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.28%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.86% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 1 191 visualizaciones. En el primer día suele acumular 451 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
  • Intereses temáticos: El contenido se centra en temas clave como array, stack, algorithm, programming, sort.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
This channel contains the free resources and solution of coding problems which are usually asked in the interviews. Managed by: @love_data

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 12 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.

52 139
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+524 horas
+257 días
+14830 días
Archivo de publicaciones
Expert resumes for managers and executives Wendy Enelow, 2012

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1_Power BI interview questions.pdf7.09 KB

Data Structure and Algorithm Notes-1.pdf5.50 MB

11 Data Structures used in daily life
11 Data Structures used in daily life

Most Asked Python Interview Questions with Answers

Master 20+ skills for just 99/Year 💰150+ courses to learn from 📺Access to Live workshops 📚Interview Preparation 💼Access t
Master 20+ skills for just 99/Year 💰150+ courses to learn from 📺Access to Live workshops 📚Interview Preparation 💼Access to exclusive EdYoda JOB PORTAL 📜Download 150+ Course completion certificates Start now: https://bit.ly/3OGOVE8 Offer valid for limited time only!

Software Development from A to Z Olga Filipova, 2019

Bard AI by Google is finally out 🚀 Try it here: https://bard.google.com Bard AI python API : https://github.com/dsdanielpark/BARD_API

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spring-interview-questions 1.pdf7.54 KB

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Machine Learning for Absolute Beginners Oliver Theobald, 2020

Sorting Algorithms
Sorting Algorithms

Most Asked Interview Questions with Answers 💻✅
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Most Asked Interview Questions with Answers 💻✅

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Chatgpt prompt
Chatgpt prompt

*Type of problem, wile solving DSA problem in Array* ❗ There are many types of problems that can be solved using arrays and different techniques in Data Structures and Algorithms. Here are some common problem types and techniques that you might encounter: 𝟏. 𝐒𝐥𝐢𝐝𝐢𝐧𝐠 𝐰𝐢𝐧𝐝𝐨𝐰 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: In these problems, you are given an array and a window size, and you have to find a subarray of that size that satisfies certain conditions. You can use a sliding window technique to efficiently search through the array by maintaining a current window of fixed size and updating it as you move forward. 𝟐. 𝐓𝐰𝐨 𝐩𝐨𝐢𝐧𝐭𝐞𝐫 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: In these problems, you use two pointers to traverse the array from both ends and find a certain pattern or condition. For example, you can use two pointers to find a pair of elements that sum up to a target value, or to reverse an array. 𝟑. 𝐒𝐨𝐫𝐭𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: In these problems, you are asked to sort an array in a certain way, such as in ascending or descending order, or according to certain criteria such as frequency or value. You can use sorting algorithms such as merge sort or quick sort to efficiently sort the array. 𝟒. 𝐒𝐞𝐚𝐫𝐜𝐡𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: In these problems, you are asked to find a specific element in the array or to search for a certain pattern. You can use searching algorithms such as binary search or linear search to efficiently search through the array. 𝟓. 𝐒𝐮𝐛𝐚𝐫𝐫𝐚𝐲 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: In these problems, you are asked to find a contiguous subarray that satisfies certain conditions. You can use techniques such as prefix sum or Kadane's algorithm to efficiently find the subarray with the maximum sum. 𝟔. 𝐂𝐨𝐮𝐧𝐭𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: In these problems, you are asked to count the occurrences of certain elements or to count the number of subarrays or subsequences that satisfy certain conditions. You can use techniques such as hashing or dynamic programming to efficiently count the occurrences or number of subarrays.

MongoDB - Python.pdf7.58 KB