Here's how you can choose the best programming languages to learn algorithm skills.

Your journey depends on your goals and aspirations. Here are some suggestions to help you get started: If you aspire to become a Data Scientist, Machine Learning Engineer, or Artificial Intelligence Engineer, consider starting with Python. It is beginner-friendly and widely used in these fields. If you want to become a Web Developer, you might choose Java, C#, or JavaScript. If you aim to be a Statistician, Business Analyst, or Data Analyst, R could be a good choice. Generally, Python is an excellent option for beginners due to its simplicity and versatility. Select a language based on your convenience and the specific requirements of your career path.

Data Structures and Algorithms are important aspect of software Engineering. And these are independent on programming language. Hence, language is just way of coding in such a way respective to that particular guidelines and syntax. So try to understand the underlying working of algorithms and data structures so that you can eventually code. When it comes to selecting programming language. Use the following: ?? Interested in AI, ML, Data related roles and aspects, Automation, dealing with DataSets ?? Python ?? Interested in mobile applications, Android, Enterprise field ??choose Java, C# ??Interested in embedded world, working with low level aspects ??choose C/C++

Choosing the right programming language can significantly influence your journey in learning algorithms. Different types of programming languages offer various advantages and challenges, shaping your understanding and approach to algorithmic problem-solving.

Language doesn't matter specially in algorithm. What's more important is how you are good at problem solving or finding solutions to any problem, language comes after algorithms.

I actually discourage newcomers from choosing Python as their first programming language. I've seen too many examples of people starting from Python, and then really struggling to get the right thinking needed for operating less high-level and less simplified languages. This often leads to frustration and abandonment of the programming as whole. Starting off with a dynamically-typed language with implicit memory management and (over) simplified syntax can be perfect if you do Math or some Engineering (not the software one), but it may really close some doors in software development for you. I would recommend starting with C/C++ as I personally did, or consider Rust - it is modern but gives you complete understanding and control.

In my experience as a systems developer, I believe that regardless of the language used or technology assigned, clean and well-structured code together with an organized design pattern with an easy-to-understand architecture is crucial for the maintenance and development of successful projects.

When learning algorithms, performance and speed are crucial considerations. Languages like Python, while user-friendly, may not offer optimal runtime performance compared to more complex syntax languages like C, C++ or Java. Regardless of your language choice, prioritize efficient code organization and adopt the most effective problem-solving approaches. Efficiency in coding is key, ensuring your algorithms perform optimally, regardless of the language's inherent speed characteristics.

State-of-the-art work on algorithms is no longer developed, implemented or tested alone. Most of the valuable new algorithms are built on top of the existing solutions. And when it comes to cutting-edge AI technologies, it is getting increasingly harder for one single person or even a team that is isolated from the world to produce anything of value - if they are not relying on community support. An example of community support is an open-source library. Standing on the shoulders of giants is no longer the way to produce science, standing on the shoulders of communities is!

I believe that the best way to learn something so complex is by putting your studies into practice and carrying out personal projects by sharing them on platforms and in communication forums focused on the area. Of course, with great effort and a supportive community, we all come out ahead.

I have to say that the best thing that has happened to my programming career was my introduction to the open source community. Fact that almost all the big business software use open source somewhere in their stack shows how powerful this community is. Apart from this just the sheer enthusiasm that people on stack overflow show towards programming by forming a community is captivating. No wonder I visit these more than I thought I would.

When I began coding, I worked independently, often spending significant time solving issues alone. Discovering coding communities like StackOverflow, github, leetcode transformed my approach. Opt for languages with robust community support; they provide invaluable help when you encounter challenges.

The amount of learning resources available online is just so mind blowing and inspiring. I would say every time I have a bad mood I just open up a programming video on YouTube/MIT and start watching it. It gives me so much joy to learn for free. Apart from this community of developers always ready to help each other can create such a welcoming environment for anyone starting to learn programming!

Access to educational resources is crucial for learning programming. While platforms like YouTube offer free content, I recommend starting with official documentation before diving into online videos. This ensures a solid foundation and clear understanding of concepts before exploring supplementary materials.

If you want paid well structured course then go with - Programming Pathshala. If you want free then go with - TakeYouForward, or GeeksForGeeks.

Practical Application of Programming Languages The best way to learn a language is to create projects using it. Choosing the right language for your project can be daunting with so many options available. Here’s a guide: Web Development (Frontend): JavaScript ??, TypeScript ?? Web Development (Backend): Python ??, Node.js ??, Java Data Science: Python ?? Mobile App Development: Swift ??, Kotlin ?? Game Development: C++ ??, C# ?? Desktop Applications: Java ??, C# ?? Embedded Systems: C/C++ ?? Blockchain: Solidity ??, JavaScript ?? AI and NLP: Python ?? System Administration: Bash ???, Python ?? Choosing based on project needs, team expertise, and community support ensures a solid foundation for success.

- ?? Consider practical application when choosing programming languages for algorithm skills. - ?? For web development, JavaScript is ideal due to its dominance in the space. - ?? For backend development or enterprise applications, Java's robust ecosystem and portability are beneficial. - ?? Align your language choice with your career goals to maximize the relevance of your learning. - ?? Ensure that learning algorithms also builds expertise in a language relevant to your desired field. - ?? Focus on languages that will directly benefit your professional aspirations and projects. - ?? This targeted approach optimizes your time investment and enhances career prospects.

One thing I have found useful is to learn with projects and apply your skills or newly acquired experience and knowledge in a hands on project to deepen your understanding and keep the zeal going on and the hunger for more with the burning desire to explore all objectives and solutions.

Go with that language which you know very well like java ,python etc. Just make it simple with what you know already Make a list of all Algorithms And learn about it and practice as much as you can , and relate with it's real time examples