In this article, you will be getting knowledge in Programming Languages For Data Scientists in 2023. Despite the growing importance of no-code and low-code platforms, programming and coding by hand are still quite important. This is especially important for data science professionals. However, there is a learning curve for data scientists. Along with coding, they will also need to unlearn and relearn math and business, and various other elements of thought leadership that they may have never considered before.
Apart from these, data scientists have to choose the latest programming languages which are widely accepted by cutting edge technologies and offer rich features. Programming languages are high-level languages for data science, and those who wish to enter this growing field must be proficient in these languages to gain an edge over their competitors. In this article, we have listed the top 7 programming languages for data scientists to learn in 2023.
Python has the highest popularity among data scientists, mainly due to its wide range of applications across all domains. Various tasks based on DL (Deep Learning), ML (Machine learning), AI(Artificial intelligence), and other popular forms of technology can be easily handled through Python. Language libraries like Keras, sci-kit-learn, and TensorFlow offer tremendous opportunities for advancement.
Java is an open sourced and object-oriented programming language and one of the most popular in the world, used for data science purposes. Due to its top-notch performance and efficiency, Java has become one of the popular programming languages in the data science industry.
SQL is one of the great for data management and handling. Although the language is not specifically used for data science operations, knowledge of SQL tables and queries can help data scientists deal with database management systems. The language is particularly domain-oriented and extremely convenient for storing, manipulating, and retrieving data in relational databases.
Scala is a modern programming language that has gained prominence in the data science industry in recent years. These applications range from web programming to ML (Machine learning). The language is highly scalable and effective in handling large data sets. Modern organizations using Scala benefit from object-oriented and functional programming, as well as concurrent and synchronized processing.
Julia is a data science programming language developed specifically for fast numerical analysis and high-performance computational science. You can quickly introduce math concepts like linear algebra, and you’re excellent at working with matrices.
Go is a new programming language that has gained prominence in the data science industry. It is a language that addresses important questions in Python. Go excels at reading and manipulating data and is widely used by experienced data scientists around the world.
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