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Coding is tricky. Coding in interviews feels even harder. It’s intimidating, uncertain and hard to prepare. Here are 4 ways to do it! 1. Interview Cake: I think it is some of the best prep available and it is targeted toward weaknesses many data scientists have in algorithms and data structures: https://www.interviewcake.com/ 2. Leetcode: While developed for software engineering interviews, it has a LOT of useful content for learning algorithms. For data science, I'd suggest focusing on Easy/Medium: https://leetcode.com/ 3. Cracking the Coding Interview: Amazing book, sometimes referred to as CTCI. A classic and one you should have: https://cin.ufpe.br/~fbma/Crack/Cracking%20the%20Coding%20Interview%20189%20Programming%20Questions%20and%20Solutions.pdf 4. Daily Coding Problem: The book and the website are awesome. Work on a daily problem. This was my go to resource for when I was looking to stay sharp: https://www.dailycodingproblem.com/

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7 popular programming languages and their benefits: 1. Python: - Benefits: Python is known for its simplicity and readability, making it a great choice for beginners. It has a vast ecosystem of libraries and frameworks for various applications such as web development, data science, machine learning, and automation. Python's versatility and ease of use make it a popular choice for a wide range of projects. 2. JavaScript: - Benefits: JavaScript is the language of the web, used for building interactive and dynamic websites. It is supported by all major browsers and has a large community of developers. JavaScript can also be used for server-side development (Node.js) and mobile app development (React Native). Its flexibility and wide range of applications make it a valuable language to learn. 3. Java: - Benefits: Java is a robust, platform-independent language commonly used for building enterprise-level applications, mobile apps (Android), and large-scale systems. It has strong support for object-oriented programming principles and a rich ecosystem of libraries and tools. Java's stability, performance, and scalability make it a popular choice for building mission-critical applications. 4. C++: - Benefits: C++ is a powerful and efficient language often used for system programming, game development, and high-performance applications. It provides low-level control over hardware and memory management while offering high-level abstractions for complex tasks. C++'s performance, versatility, and ability to work closely with hardware make it a preferred choice for performance-critical applications. 5. C#: - Benefits: C# is a versatile language developed by Microsoft and commonly used for building Windows applications, web applications (with ASP.NET), and games (with Unity). It offers a modern syntax, strong type safety, and seamless integration with the .NET framework. C#'s ease of use, robustness, and support for various platforms make it a popular choice for developing a wide range of applications. 6. R: - Benefits: R is a language specifically designed for statistical computing and data analysis. It has a rich set of built-in functions and packages for data manipulation, visualization, and machine learning. R's focus on data science, statistical modeling, and visualization makes it an ideal choice for researchers, analysts, and data scientists working with large datasets. 7. Swift: - Benefits: Swift is Apple's modern programming language for developing iOS, macOS, watchOS, and tvOS applications. It offers safety features to prevent common programming errors, high performance, and interoperability with Objective-C. Swift's clean syntax, powerful features, and seamless integration with Apple's platforms make it a preferred choice for building native applications in the Apple ecosystem. These are just a few of the many programming languages available today, each with its unique strengths and use cases. Credits: https://t.me/free4unow_backup Like if you need similar content 😄👍

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🔟 𝘁𝗶𝗽𝘀 𝗳𝗼𝗿 𝗻𝗲𝘄 𝗰𝗼𝗱𝗲𝗿𝘀: 🔖 1. Learn Fundamentals:  Use W3Schools, FreeCodeCamp, or MDN for solid basics. 2. Watch and Code Along:  Follow YouTube tutorials to code in real-time. 3. Practice Regularly:  Build small projects to sharpen your skills. 4. Join Coding Communities:  Engage on platforms like X, Discord, and Reddit for support. 5. Use AI Tools Wisely: Leverage tools like ChatGPT responsibly to aid learning. 6. Master Git and Version Control:  Learn to manage your code effectively. 7. Stay Updated:  Follow tech blogs, newsletters, and podcasts. 8. Network:  Attend meetups, hackathons, and online coding events. 9. Explore Open Source:  Contribute to projects to gain experience. 10.Never Stop Learning:  Technology evolves—keep exploring new languages and frameworks. Best Programming Resources: https://topmate.io/coding/886839 All the best 👍👍

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

Famous programming languages and their frameworks 1. Python: Frameworks: Django Flask Pyramid Tornado 2. JavaScript: Frameworks (Front-End): React Angular Vue.js Ember.js Frameworks (Back-End): Node.js (Runtime) Express.js Nest.js Meteor 3. Java: Frameworks: Spring Framework Hibernate Apache Struts Play Framework 4. Ruby: Frameworks: Ruby on Rails (Rails) Sinatra Hanami 5. PHP: Frameworks: Laravel Symfony CodeIgniter Yii Zend Framework 6. C#: Frameworks: .NET Framework ASP.NET ASP.NET Core 7. Go (Golang): Frameworks: Gin Echo Revel 8. Rust: Frameworks: Rocket Actix Warp 9. Swift: Frameworks (iOS/macOS): SwiftUI UIKit Cocoa Touch 10. Kotlin: - Frameworks (Android): - Android Jetpack - Ktor 11. TypeScript: - Frameworks (Front-End): - Angular - Vue.js (with TypeScript) - React (with TypeScript) 12. Scala: - Frameworks: - Play Framework - Akka 13. Perl: - Frameworks: - Dancer - Catalyst 14. Lua: - Frameworks: - OpenResty (for web development) 15. Dart: - Frameworks: - Flutter (for mobile app development) 16. R: - Frameworks (for data science and statistics): - Shiny - ggplot2 17. Julia: - Frameworks (for scientific computing): - Pluto.jl - Genie.jl 18. MATLAB: - Frameworks (for scientific and engineering applications): - Simulink 19. COBOL: - Frameworks: - COBOL-IT 20. Erlang: - Frameworks: - Phoenix (for web applications) 21. Groovy: - Frameworks: - Grails (for web applications)

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You could completely change your life by the end of this year. You could take another job, start learning a new language or skill, cut out junk food and start working out. You can do anything! You have 100% control over your life. Sometimes it doesn't feel like it. Like your life is passing you by, but you could make huge changes today that could effect the rest of your life. Make a plan and do it!

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10 tips to level down as a software engineer These secret top tips will make you a "10x engineer": ☐ Never Test Your Code: Just ship it. Users will find the bugs for you. ☐ Overcomplicate Everything: Simple solutions are for simple people. ☐ Never Ask Questions: Questions are weakness. Figure it out, even if it takes days. ☐ Embrace Spaghetti Code: If nobody understands, they can’t replace you. ☐ Ignore PR Feedback: Don’t waste time with reviews. Your code is perfect as is. ☐ Only Use ChatGPT: Copy, paste, clock out. Understanding is overrated. ☐ Forget Naming Conventions: x, xx, xxx are perfectly clear variable names. ☐ Hoard Knowledge: Documentation? That’s your job security right there. ☐ Optimise Prematurely: Make it faster, at any cost. ☐ Deploy on Fridays at 5 PM: Weekend plans are for people who don’t love their job.

The urge to leave this rat race behind and just enjoy a simple, slow life is something I feel more and more. Sometimes, it feels like slowing down is exactly what we need to really start living.💫💫

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Leetcode is a tool to learn Neetcode is a tool to learn CodeChef is a tool to learn Codeforces is a tool to learn HackerRank is a tool to learn GeeksForGeeks is a tool to learn It doesn't matter: - which platform you are using - or how many problems you solve All that matters is how strong you grasp concepts and adapt to problems. Don't chase the status of 500 or 1000 problems solved. Chase proper learning & training your mind for problem-solving. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

Junior Developer: - Doesn't know Regex - Doesn't know how to test code programmatically -Doesn't know how to write good technical stories Mid Level Developer: - Doesn't know Regex - Begins to understand how to test code programmatically - Begins to understand how to write good technical stories Senior Developer: - Doesn't know Regex - Understands how to test code programmatically - Understands how to write good technical stories