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.

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.

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

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

3. Cracking the Coding Interview:

Amazing book, sometimes referred to as CTCI. A classic and one you should have:

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