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Coders Learning

Coders Learning

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We provide Webinars, Jobs, Resources, Books, Notes, and Unlimited Free Courses with CERTIFICATES!β˜‘οΈ For Promotions: Mail: coderslearning07@gmail.com Join us on WhatsApp!πŸ‘‡ β€Žhttps://whatsapp.com/channel/0029Vajh8uc2ER6gzBxUYs1U

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πŸ“ˆ Analytical overview of Telegram channel Coders Learning

Channel Coders Learning (@coderslearning) in the English language segment is an active participant. Currently, the community unites 32 575 subscribers, ranking 5 924 in the Education category and 12 172 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 32 575 subscribers.

According to the latest data from 27 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -359 over the last 30 days and by -8 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 4.17%. Within the first 24 hours after publication, content typically collects 1.19% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 360 views. Within the first day, a publication typically gains 388 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
  • Thematic interests: Content is focused on key topics such as |--, sql, engineer, developer, hcl.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œWe provide Webinars, Jobs, Resources, Books, Notes, and Unlimited Free Courses with CERTIFICATES!β˜‘οΈ For Promotions: Mail: coderslearning07@gmail.com Join us on WhatsApp!πŸ‘‡ β€Žhttps://whatsapp.com/channel/0029Vajh8uc2ER6gzBxUYs1U”

Thanks to the high frequency of updates (latest data received on 28 October, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

32 575
Subscribers
-824 hours
-797 days
-35930 days
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Complete roadmap to learn Python and Data Structures & Algorithms (DSA) in 2 months ### Week 1: Introduction to Python Day 1-2: Basics of Python - Python setup (installation and IDE setup) - Basic syntax, variables, and data types - Operators and expressions Day 3-4: Control Structures - Conditional statements (if, elif, else) - Loops (for, while) Day 5-6: Functions and Modules - Function definitions, parameters, and return values - Built-in functions and importing modules Day 7: Practice Day - Solve basic problems on platforms like HackerRank or LeetCode ### Week 2: Advanced Python Concepts Day 8-9: Data Structures in Python - Lists, tuples, sets, and dictionaries - List comprehensions and generator expressions Day 10-11: Strings and File I/O - String manipulation and methods - Reading from and writing to files Day 12-13: Object-Oriented Programming (OOP) - Classes and objects - Inheritance, polymorphism, encapsulation Day 14: Practice Day - Solve intermediate problems on coding platforms ### Week 3: Introduction to Data Structures Day 15-16: Arrays and Linked Lists - Understanding arrays and their operations - Singly and doubly linked lists Day 17-18: Stacks and Queues - Implementation and applications of stacks - Implementation and applications of queues Day 19-20: Recursion - Basics of recursion and solving problems using recursion - Recursive vs iterative solutions Day 21: Practice Day - Solve problems related to arrays, linked lists, stacks, and queues ### Week 4: Fundamental Algorithms Day 22-23: Sorting Algorithms - Bubble sort, selection sort, insertion sort - Merge sort and quicksort Day 24-25: Searching Algorithms - Linear search and binary search - Applications and complexity analysis Day 26-27: Hashing - Hash tables and hash functions - Collision resolution techniques Day 28: Practice Day - Solve problems on sorting, searching, and hashing ### Week 5: Advanced Data Structures Day 29-30: Trees - Binary trees, binary search trees (BST) - Tree traversals (in-order, pre-order, post-order) Day 31-32: Heaps and Priority Queues - Understanding heaps (min-heap, max-heap) - Implementing priority queues using heaps Day 33-34: Graphs - Representation of graphs (adjacency matrix, adjacency list) - Depth-first search (DFS) and breadth-first search (BFS) Day 35: Practice Day - Solve problems on trees, heaps, and graphs ### Week 6: Advanced Algorithms Day 36-37: Dynamic Programming - Introduction to dynamic programming - Solving common DP problems (e.g., Fibonacci, knapsack) Day 38-39: Greedy Algorithms - Understanding greedy strategy - Solving problems using greedy algorithms Day 40-41: Graph Algorithms - Dijkstra’s algorithm for shortest path - Kruskal’s and Prim’s algorithms for minimum spanning tree Day 42: Practice Day - Solve problems on dynamic programming, greedy algorithms, and advanced graph algorithms ### Week 7: Problem Solving and Optimization Day 43-44: Problem-Solving Techniques - Backtracking, bit manipulation, and combinatorial problems Day 45-46: Practice Competitive Programming - Participate in contests on platforms like Codeforces or CodeChef Day 47-48: Mock Interviews and Coding Challenges - Simulate technical interviews - Focus on time management and optimization Day 49: Review and Revise - Go through notes and previously solved problems - Identify weak areas and work on them ### Week 8: Final Stretch and Project Day 50-52: Build a Project - Use your knowledge to build a substantial project in Python involving DSA concepts Day 53-54: Code Review and Testing - Refactor your project code - Write tests for your project Day 55-56: Final Practice - Solve problems from previous contests or new challenging problems Day 57-58: Documentation and Presentation - Document your project and prepare a presentation or a detailed report Day 59-60: Reflection and Future Plan - Reflect on what you've learned - Plan your next steps (advanced topics, more projects, etc.) Join @coderslearning for more! βœ… ENJOY LEARNING πŸ‘πŸ‘

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Trending Tech Stacks in 2025πŸ‘‡πŸ‘‡ 1. Frontend Development:    - React.js: Known for its component-based architecture and strong community support.    - Vue.js: Valued for its simplicity and flexibility in building user interfaces.    - Angular: Still widely used, especially in enterprise applications. 2. Backend Development:    - Node.js: Popular for building scalable and fast network applications using JavaScript.    - Django: Preferred for its rapid development capabilities and robust security features.    - Spring Boot: Widely used in Java-based applications for its ease of use and integration capabilities. 3. Mobile Development:    - Flutter: Known for building natively compiled applications for mobile, web, and desktop from a single codebase.    - React Native: Continues to be popular for building cross-platform applications with native capabilities. 4. Cloud Computing and DevOps:    - AWS (Amazon Web Services), Azure, Google Cloud: Leading cloud service providers offering extensive services for computing, storage, and networking.    - Docker and Kubernetes: Essential for containerization and orchestration of applications in a cloud-native environment.    - Terraform: Infrastructure as code tool for managing and provisioning cloud infrastructure. 5. Data Science and Machine Learning:    - Python: Dominant language for data science and machine learning, with libraries like NumPy, Pandas, and Scikit-learn.    - TensorFlow and PyTorch: Leading frameworks for building and training machine learning models.    - Apache Spark: Used for big data processing and analytics. 6. Cybersecurity:    - SIEM Tools (Security Information and Event Management): Such as Splunk and ELK Stack, crucial for monitoring and managing security incidents.    - Zero Trust Architecture: A security model that eliminates the idea of trust based on network location. 7. Blockchain and Cryptocurrency:    - Ethereum: A blockchain platform supporting smart contracts and decentralized applications.    - Hyperledger Fabric: Framework for developing permissioned, blockchain-based applications. 8. Artificial Intelligence (AI) and Natural Language Processing (NLP):    - GPT (Generative Pre-trained Transformer) Models: Such as GPT-4, used for various natural language understanding tasks.    - Computer Vision: Frameworks like OpenCV for image and video processing tasks. 9. Edge Computing and IoT (Internet of Things):    - Edge Computing: Technologies that bring computation and data storage closer to the location where it is needed.    - IoT Platforms: Such as AWS IoT, Azure IoT Hub, offering capabilities for managing and securing IoT devices and data. Join @coderslearning for more βœ… ENJOY LEARNING πŸ‘πŸ‘

Important skills every self-taught developer should master: πŸ’» HTML, CSS & JavaScript β€” the foundation of web development βš™οΈ Git & GitHub β€” track changes and collaborate effectively 🧠 Problem-solving β€” break down and debug complex issues πŸ—„οΈ Basic SQL β€” manage and query data efficiently 🧩 APIs β€” fetch and use data from external sources 🧱 Frameworks β€” like React, Flask, or Django to build faster 🧼 Clean Code β€” write readable, maintainable code πŸ“¦ Package Managers β€” like npm or pip for managing libraries πŸš€ Deployment β€” host your projects for the world to see Join @coderslearning for more! βœ…

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Python Detailed Roadmap πŸš€ πŸ“Œ 1. Basics β—Ό Data Types & Variables β—Ό Operators & Expressions β—Ό Control Flow (if, loops) πŸ“Œ 2. Functions & Modules β—Ό Defining Functions β—Ό Lambda Functions β—Ό Importing & Creating Modules πŸ“Œ 3. File Handling β—Ό Reading & Writing Files β—Ό Working with CSV & JSON πŸ“Œ 4. Object-Oriented Programming (OOP) β—Ό Classes & Objects β—Ό Inheritance & Polymorphism β—Ό Encapsulation πŸ“Œ 5. Exception Handling β—Ό Try-Except Blocks β—Ό Custom Exceptions πŸ“Œ 6. Advanced Python Concepts β—Ό List & Dictionary Comprehensions β—Ό Generators & Iterators β—Ό Decorators πŸ“Œ 7. Essential Libraries β—Ό NumPy (Arrays & Computations) β—Ό Pandas (Data Analysis) β—Ό Matplotlib & Seaborn (Visualization) πŸ“Œ 8. Web Development & APIs β—Ό Web Scraping (BeautifulSoup, Scrapy) β—Ό API Integration (Requests) β—Ό Flask & Django (Backend Development) πŸ“Œ 9. Automation & Scripting β—Ό Automating Tasks with Python β—Ό Working with Selenium & PyAutoGUI πŸ“Œ 10. Data Science & Machine Learning β—Ό Data Cleaning & Preprocessing β—Ό Scikit-Learn (ML Algorithms) β—Ό TensorFlow & PyTorch (Deep Learning) πŸ“Œ 11. Projects β—Ό Build Real-World Applications β—Ό Showcase on GitHub πŸ“Œ 12. βœ… Apply for Jobs β—Ό Strengthen Resume & Portfolio β—Ό Prepare for Technical Interviews Join @coderslearning for more! βœ…

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Game Development Roadmap | | |-- Fundamentals | |-- Introduction to Game Development | | |-- Types of Games (2D, 3D, Mobile, VR) | | |-- Game Development Life Cycle | |-- Game Design Basics | | |-- Game Mechanics | | |-- Storytelling in Games | | |-- User Experience (UX) in Games | |-- Game Engines | |-- Unity | | |-- Understanding the Interface | | |-- Scripting with C# | | |-- Physics and Animation | |-- Unreal Engine | | |-- Understanding Blueprints | | |-- C++ Programming | |-- Godot | | |-- Game Scene Development | | |-- GDScript Basics | |-- Game Programming | |-- Programming Languages | | |-- C++ (Unreal Engine) | | |-- C# (Unity) | | |-- Python (Prototyping and Scripting) | |-- Game Loop and Event Handling | | |-- Game State Management | | |-- Input Handling (Keyboard, Mouse, Touch, etc.) | |-- 2D Game Development | |-- Game Mechanics for 2D | | |-- Collision Detection | | |-- Physics Simulation | | |-- Movement and Animation | |-- Graphics and Art | | |-- Sprite Animation | | |-- Tile-based Level Design | |-- 3D Game Development | |-- 3D Modeling and Animation | | |-- Using Blender for 3D Assets | | |-- Rigging and Skinning | |-- 3D Physics | | |-- Rigidbody Dynamics | | |-- Collisions in 3D Space | |-- Camera Systems | | |-- First-person and Third-person Cameras | | |-- Camera Interpolation and Smoothness | |-- Game Audio | |-- Sound Effects | | |-- Creating and Implementing SFX | | |-- Audio Design in Games | |-- Background Music | | |-- Dynamic Soundtracks | | |-- Adaptive Music for Game Events | |-- Artificial Intelligence in Games | |-- AI for NPCs | | |-- Pathfinding (A* Algorithm) | | |-- State Machines and Behavior Trees | |-- Procedural Content Generation | |-- AI for Opponents | | |-- Combat AI | | |-- Strategy AI | |-- Multiplayer Game Development | |-- Networking Basics | | |-- Client-Server Architecture | | |-- Real-time Multiplayer Games | |-- Matchmaking and Server Architecture | | |-- Peer-to-peer Networking | | |-- Dedicated Servers | |-- Game Monetization | |-- In-App Purchases | | |-- Virtual Goods and Currency | | |-- Ad Integration | |-- Game Distribution | | |-- Steam, Epic Games Store, and App Stores | | |-- Publishing and Marketing Strategies | |-- Virtual Reality (VR) and Augmented Reality (AR) Development | |-- VR/AR Basics | | |-- Oculus Rift and HTC Vive Development | | |-- Unity/Unreal for VR/AR | |-- Interaction Design for VR/AR | | |-- Hand Tracking and Gesture Recognition | | |-- Immersive Environment Design | |-- Game Testing and Debugging | |-- Quality Assurance (QA) | | |-- Playtesting and Feedback | | |-- Bug Tracking and Fixing | |-- Performance Optimization | | |-- Reducing Load Times and Memory Usage | | |-- Frame Rate Optimization | |-- Game Publishing and Marketing | |-- Game Release Strategies | | |-- Early Access and Beta Testing | | |-- Launch Planning and Publicity | |-- Community Engagement | | |-- Building a Player Community | | |-- Social Media and Influencer Marketing React with β™₯️ if you also want free resources on this topic Join @coderslearning for more! βœ…

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Resume Tips for Developers – What to Add & Avoid A well-structured resume can help you land interviews faster. Follow these tips to create a strong, ATS-friendly resume. πŸ”Ή Header (Top of Resume) βœ… Full Name (No nicknames) βœ… Job Title (Example: Full Stack Developer) βœ… Professional Email & Phone Number βœ… Location (City, Country) βœ… LinkedIn & GitHub Profile βœ… Portfolio/Website (if available) ❌ No fancy fonts, colors, or personal details (age, gender, marital status) πŸ”Ή Summary (Short & Powerful) βœ… 3-4 lines about experience, skills & achievements βœ… Mention years of experience & tech stack Example: πŸš€ Software Engineer with 4+ years of experience in building scalable backend systems using Node.js, MongoDB & AWS. Reduced API response time by 40% & improved deployment efficiency. ❌ Avoid first-person writing ("I am a developer") πŸ”Ή Technical Skills (ATS Optimization) βœ… List relevant programming languages, frameworks, databases, cloud & DevOps tools Example: makefile Copy Edit Programming: JavaScript, Python, C++ Frameworks: React, Node.js, Django Databases: MongoDB, PostgreSQL Cloud: AWS, Docker, Kubernetes ❌ Avoid listing skills you haven’t worked with πŸ”Ή Work Experience (Show Impact) βœ… Use reverse chronological order βœ… Highlight achievements with numbers Example: πŸš€ Backend Developer | XYZ Tech | Jan 2022 - Present Developed REST APIs using Node.js & Express, reducing response time by 35% Integrated MongoDB, improving database query efficiency by 40% Implemented JWT & OAuth authentication systems ❌ Don’t copy-paste job descriptions without impact πŸ”Ή Projects (Showcase Real Work) βœ… Mention tech stack & impact βœ… Add GitHub & Live Demo links Example: πŸš€ AI Resume Analyzer | Python, Flask, TensorFlow Built an AI-powered resume parser that serves 5K+ users per month Used NLP algorithms to extract skills & experience GitHub Link: [Insert Link] | Live Demo: [Insert Link] ❌ Don’t list simple projects like a to-do app πŸ”Ή Education & Certifications βœ… Degree | University | Year βœ… Relevant certifications (AWS, Google Cloud, Microsoft) ❌ No need to list high school if you have a degree πŸ”Ή What to Avoid in Your Resume ❌ Long resumes (Keep it 1 page, max 2 if 5+ years experience) ❌ Fancy formatting & graphics (Use Arial, Calibri, Roboto) ❌ Personal details like photo, age, gender ❌ Grammar mistakes (Use Grammarly) ❌ Fake experience or skills πŸ”Ή ATS-Friendly Formatting βœ… Fonts: Arial, Calibri, Roboto (Size 11-12) βœ… Use job-specific keywords from descriptions βœ… Avoid tables & graphics (ATS can’t read them) βœ… Save as PDF Follow these tips to create a resume that gets noticed! πŸš€ Join @coderslearning for more! βœ…

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SQL Interview Questions! πŸ”₯πŸš€ Basic SQL Interview Questions: - What is SQL? - What are the different types of SQL commands? - What is the difference between DDL, DML, DCL, and TCL? - What is the difference between SQL and MySQL? - What is a primary key? - What is a foreign key? - What is a unique key? - What is the difference between primary key and unique key? - What is the difference between HAVING and WHERE? - What are constraints in SQL? Name a few. - What is the difference between CHAR and VARCHAR? - What is Normalization? What are its types? - What is Denormalization? - What is an index in SQL? - What are the different types of indexes? - What is the difference between Clustered and Non-clustered indexes? - What is an alias in SQL? - What is the difference between DELETE and TRUNCATE? - What is the difference between TRUNCATE and DROP? - What is a view in SQL? ------------------------------------- Intermediate SQL Interview Questions: What is a self-join? What is an inner join? What is the difference between INNER JOIN and OUTER JOIN? What are the types of OUTER JOIN? What is a cross join? What is a Cartesian join? What is the difference between UNION and UNION ALL? What is the difference between JOIN and UNION? What is a stored procedure? What is a trigger in SQL? What are the different types of triggers? What is the difference between HAVING and GROUP BY? What are subqueries? What are correlated subqueries? What is an EXISTS clause in SQL? What is the difference between EXISTS and IN? What is a cursor in SQL? What is the difference between OLTP and OLAP? What are ACID properties in SQL? What is normalization? Explain 1NF, 2NF, 3NF, and BCNF. What is a composite key? What is a surrogate key? What is the use of the COALESCE function? What is the difference between IS NULL and IS NOT NULL? What is partitioning in SQL? ------------------------------------- Advanced SQL Interview Questions: What are window functions in SQL? What is CTE (Common Table Expression)? What is the difference between TEMP TABLE and CTE? What is the difference between RANK(), DENSE_RANK(), and ROW_NUMBER()? What is a materialized view? What is the difference between materialized views and normal views? What is sharding in SQL? What is the MERGE statement? What is the JSON data type in SQL? What is recursive CTE? What is the difference between LEFT JOIN and LEFT OUTER JOIN? How does indexing impact performance? What is the difference between OLAP and OLTP? What is ETL (Extract, Transform, Load)? What are window functions? Explain LEAD, LAG, and NTILE. What is a pivot table in SQL? What is Dynamic SQL? What is a NoSQL database? How is it different from SQL databases? What is the difference between SQL and PL/SQL? How to find the N-th highest salary in SQL? ------------------------------------- Practical SQL Queries: Find the second highest salary from an Employee table. Find duplicate records in a table. Write a SQL query to find the count of employees in each department. Write a query to find employees who earn more than their managers. Write a query to fetch the first three characters of a string. Write a SQL query to swap two columns in a table without using a temporary table. Write a query to find all employees who joined in the last 6 months. Write a query to find the most repeated values in a column. Write a query to delete duplicate rows from a table. Write a SQL query to find all customers who made more than 5 purchases. Join @coderslearning for more! βœ…

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