Looking for the best programming language for AI depends on the need and level of programming a person is doing. If you are a beginner then there are different sets of programming languages that you need to excel. But if a person already has some grasp as a beginner in the journey of AI, then there are more languages and skill a person will need to learn.
The best programming language for AI depends on the various factors. These factors are:
- Task Or Application a person is working on.
- Existing Tools and libraries available.
- The on going trend.
Best Programming Language for AI as Beginner
There are several programming languages that are popular since decades. AI is field that is booming now a days but the research and development for AI is going on since 1940s. There are some best programming language for AI as a beginner. If you learn the basics of those languages and some tools and libraries of the given language, you will be able to write basic to intermediate level codes for Artificial Intelligence.
List of Best Programming language for AI (Beginner):
- Python: Python is a good programming language if you are planning to start your career in AI and data science. Python can be considered as your first programming language as there are many libraries, frameworks and tools present in Python that can be used in multiple domains like Front-end, Back-end and for Databases. Python is highly recommended for beginners due to its readability and simplicity.
- R: R is a beginner friendly language. R is recommended for those who are further interested in research work which requires a deep knowledge in Data Science. R language is a suitable Language for Data Science because of its Statistical Packages.
Best Programming Language for AI as Intermediate
For Beginner to intermediate level programming, Python is a good option. But programming in only Python Language is not sufficient. One needs to learn more languages as learning other languages increases the accessibility to other important packages and libraries required for AI. If you are intermediate level of programmer in AI then below are the list of Languages and Libraries you need to learn.
- Python: As you progress as a beginner, you cannot leave Python Language. There are many Libraries, Frameworks that one needs to learn in Python for writing a good Program. You can delve deeper into Python and its popular libraries like:
- For Data Manipulation and Data Visualization: NumPy, Pandas, and Matplotlib.
- For deep learning and neural networks: TensorFlow and PyTorch.
- Java: Java is another good option. Even if you master programming language like Python, the popularity of Java can never vanish. Java is best programming language for AI as Java is used for enterprise level application. Due to robust nature of Java, one has to learn about it. It is often used in large-scale AI projects and applications. For deep learning there are libraries like Deeplearning4j.
Best Programming Language for AI as Advanced
If you are more concerned about performance, optimization and efficiency while programming in AI then there different sets of Language one needs to learn. These languages are not popular among students due to complexity of the programming language. But if one manages to learn these languages and masters it, then such languages open doors for big tech companies and product based companies like Google and Meta.
List of Best Programming Languages for AI (Advanced):
- C++: C++ is suitable for maintaining performance in critical areas of AI such as Computer Vision. It is used in AI applications that require high-performance computing, such as computer vision and game development.
- Lisp: Lisp has unique syntax and historical significance in the field of AI. It has been used in the development of symbolic reasoning systems and expert systems in previous days.
- Julia: Julia is gaining popularity among advance level of programmers. It is popular because of high-performance numerical and scientific computing. Julia is a suitable choice for those who wants a solid foundation in programming.
General Tips before starting Programming in AI
Master Fundamentals First: Before starting programming in AI, choose a language of your choice (preferably Python) and master the basics of it. After mastering the basics, master programming fundamentals, algorithms, and data structures.
Start with High-Level Libraries: After mastering the language and data structure, go for a practical approach. Start learning High-Level Libraries and Frameworks like TensorFlow or PyTorch.
Hands-On Projects: Always work on a project. While learning any programming language, the best thing is to practice. The more you practice, more you remember the fundamentals. Apply your knowledge on projects.
General FAQ related to AI
How can a devOps team take advantage of artificial intelligence (ai)?
There are certain steps one need to follow for taking advance of artificial intelligence (ai) in devOps team:
- Use Automated Monitoring: AI can detect anomalies and generates alerts in real-time.
- By Using Predictive Analytics: AI can predict and prevent performance issues.
- Use Automated Incident Response: AI identifies and addresses incidents without manual intervention.
- CI/CD Optimization: AI has tendency to improve build and deployment processes.
- Automated Testing: AI enhances test automation and coverage.
- Capacity Planning: AI predicts resource requirements for efficient scaling.
- Chatbots for Collaboration: AI-powered chatbots assist in communication and tasks.
- Security Automation: AI automates threat detection and response.
- Log Analysis: AI detects anomalies in logs for security and operational insights.
- Release Management: AI predicts release impact and automates rollbacks.
- Infrastructure Optimization: AI can analyze usage patterns for cost-effective resource allocation.