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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Red:📈 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 51 993 suscriptores, ocupando la posición 2 570 en la categoría Tecnologías y Aplicaciones y el puesto 6 675 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 51 993 suscriptores.
Según los últimos datos del 29 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -206, 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 2.17%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.63% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 129 visualizaciones. En el primer día suele acumular 325 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 30 octubre, 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.
51 993
Suscriptores
-424 horas
-817 días
-20630 días
Archivo de publicaciones
️𝗟𝗲𝗮𝗿𝗻 𝗔𝗜 & 𝗠𝗟 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 — 𝗡𝗼 𝗣𝗿𝗶𝗼𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗡𝗲𝗲𝗱𝗲𝗱!😍
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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 👍👍
𝐏𝐚𝐲 𝐀𝐟𝐭𝐞𝐫 𝐏𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 - 𝐆𝐞𝐭 𝐏𝐥𝐚𝐜𝐞𝐝 𝐈𝐧 𝐓𝐨𝐩 𝐌𝐍𝐂'𝐬 😍
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18 Most common used Java List methods
1. add(E element) - Adds the specified element to the end of the list.
2. addAll(Collection c) - Adds all elements of the specified collection to the end of the list.
3. remove(Object o) - Removes the first occurrence of the specified element from the list.
4. remove(int index) - Removes the element at the specified position in the list.
5. get(int index) - Returns the element at the specified position in the list.
6. set(int index, E element) - Replaces the element at the specified position in the list with the specified element.
7. indexOf(Object o) - Returns the index of the first occurrence of the specified element in the list.
8. contains(Object o) - Returns true if the list contains the specified element.
9. size() - Returns the number of elements in the list.
10. isEmpty() - Returns true if the list contains no elements.
11. clear() - Removes all elements from the list.
12. toArray() - Returns an array containing all the elements in the list.
13. subList(int fromIndex, int toIndex) - Returns a view of the portion of the list between the specified fromIndex, inclusive, and toIndex, exclusive.
14. addAll(int index, Collection c) - Inserts all elements of the specified collection into the list, starting at the specified position.
15. iterator() - Returns an iterator over the elements in the list.
16. sort(Comparator c) - Sorts the elements of the list according to the specified comparator.
17. replaceAll(UnaryOperator operator) - Replaces each element of the list with the result of applying the given operator.
18. forEach(Consumer action) - Performs the given action for each element of the list until all elements have been processed or the action throws an exception.
𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗼 𝗖𝗿𝗮𝗰𝗸 𝗬𝗼𝘂𝗿 𝗡𝗲𝘅𝘁 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 😍
Preparing for coding interviews? These free resources will help you crack your dream job! 📌
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SQL can be simple—if you learn it the smart way..
If you’re aiming to become a data analyst, mastering SQL is non-negotiable.
Here’s a smart roadmap to ace it:
1. Basics First: Understand data types, simple queries (SELECT, FROM, WHERE). Master basic filtering.
2. Joins & Relationships: Dive into INNER, LEFT, RIGHT joins. Practice combining tables to extract meaningful insights.
3. Aggregations & Functions: Get comfortable with COUNT, SUM, AVG, MAX, GROUP BY, and HAVING clauses. These are essential for summarizing data.
4. Subqueries & Nested Queries: Learn how to query within queries. This is powerful for handling complex datasets.
5. Window Functions: Explore ranking, cumulative sums, and sliding windows to work with running totals and moving averages.
6. Optimization: Study indexing and query optimization for faster, more efficient queries.
7. Real-World Scenarios: Apply your SQL knowledge to solve real-world business problems.
The journey may seem tough, but each step sharpens your skills and brings you closer to data analysis excellence. Stay consistent, practice regularly, and let SQL become your superpower! 💪
Here you can find essential SQL Interview Resources👇
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Hope it helps :)
𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗟𝗶𝗸𝗲 𝗜𝗻𝗳𝗼𝘀𝘆𝘀 , 𝗚𝗲𝗻𝗽𝗮𝗰𝘁 ,𝗟&𝗧 ,𝗣𝗵𝗶𝗹𝗶𝗽𝘀 & 𝗢𝗿𝗮𝗰𝗹𝗲 𝗛𝗶𝗿𝗶𝗻𝗴 😍
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𝟲 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 & 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍
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It doesn't matter:
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Chase proper learning & training your mind for problem-solving.
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Learning DSA wasn’t just about acing interviews, --- it was about thinking better, building faster, and debugging smarter.
🎯 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟵 𝗰𝗼𝗿𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝘁𝗵𝗮𝘁 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗱 𝗵𝗼𝘄 𝗜 𝘀𝗼𝗹𝘃𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀:
• Sliding Windows
• Two Pointers
• Stack Based Patterns
• Dynamic Programing
• BFS/DFS (Trees & Graphs)
• Merge Intervals
• Backtracking & Subsets
• top-k Elements (Heaps)
• Greedy Techniques
🛤️ 𝗠𝘆 𝗣𝗮𝘁𝗵 𝘁𝗼 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗗𝗦𝗔:
• Started with basic problems on arrays & strings
• Solved 1-2 problems a day, consistently for 3 months
• Focused more on patterns than individual questions
• Made my own notes, revisited problems I struggled with
• Used visual tools to understand recursion & DP
• Practiced explaining my solutions out loud (like system design reviews)
• Applied patterns in real-world projects (DevOps automation, log parsing, infra tools)
💡 𝗟𝗼𝗼𝗸𝗶𝗻𝗴 𝗯𝗮𝗰𝗸, 𝗼𝗻𝗲 𝘁𝗵𝗶𝗻𝗴 𝗶𝘀 𝗰𝗹𝗲𝗮𝗿:
> It's not how many problems you solve, it's how well you can recognize the pattern hiding in each one.
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SQL Interview Questions with Answers
1. How to change a table name in SQL?
This is the command to change a table name in SQL:
ALTER TABLE table_name
RENAME TO new_table_name;
We will start off by giving the keywords ALTER TABLE, then we will follow it up by giving the original name of the table, after that, we will give in the keywords RENAME TO and finally, we will give the new table name.
2. How to use LIKE in SQL?
The LIKE operator checks if an attribute value matches a given string pattern. Here is an example of LIKE operator
SELECT * FROM employees WHERE first_name like ‘Steven’;
With this command, we will be able to extract all the records where the first name is like “Steven”.
3. If we drop a table, does it also drop related objects like constraints, indexes, columns, default, views and sorted procedures?
Yes, SQL server drops all related objects, which exists inside a table like constraints, indexes, columns, defaults etc. But dropping a table will not drop views and sorted procedures as they exist outside the table.
4. Explain SQL Constraints.
SQL Constraints are used to specify the rules of data type in a table. They can be specified while creating and altering the table. The following are the constraints in SQL: NOT NULL CHECK DEFAULT UNIQUE PRIMARY KEY FOREIGN KEY
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𝟱 𝗙𝗿𝗲𝗲 𝗠𝗜𝗧 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗧𝗮𝗸𝗲 𝗢𝗻𝗹𝗶𝗻𝗲 — 𝗡𝗼 𝗟𝗼𝗴𝗶𝗻, 𝗡𝗼 𝗙𝗲𝗲𝘀!😍
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