![]() ![]() ![]() Python supports multiple data structures and uses a plain English syntax, making it a great language for beginner programmers. In data science, it's commonly for data processing, implementing data analytics algorithms, and training machine learning and deep learning algorithms. Python is an open source object-oriented programming language, grouping data and functions together for flexibility and composability. ![]() Learning Python opens up doors not only in data science, but also in web and software development. Python is a general purpose popular programming language. 9 Top Data Science Programming Languages 1. R and Python are popular, foundational programming languages in data science, but choosing the right language to learn depends on your level of experience, role, and/or project goals. What Programming Language Is Best for Data Science? The field of data science relies on programming across all job functions, from automating cleaning and organizing raw data sets to designing databases to fine-tuning machine learning algorithms. Use this post as a starting place to explore nine top programming languages and when they’re used in data science: While languages like Python, R, and SQL act as foundations for many data science or analytics roles, others are useful for career paths in areas such as data systems development or better suited specifically for aspiring data scientists. Programming skills are critical whichever direction you go in data science. ![]()
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