When choosing a language, you should consider your goals, the type of project you are working on, the availability of resources and support for that language, and your own level of proficiency in different languages.
The most commonly used languages in scientific research are Python, R, MATLAB, C/C++, and Java.
Some of the best languages for data analysis and visualization are Python, R, and MATLAB, as they have robust libraries and tools specifically designed for these tasks.
Python is often considered the best language for machine learning and artificial intelligence due to its extensive libraries and frameworks, such as TensorFlow and PyTorch.
It is beneficial to have knowledge of multiple languages, as each language has its own strengths and may be better suited for different tasks. However, it is also important to have a solid understanding of at least one language before branching out to others.