Top 5 Programming Languages that You Can Learn During Data Science Training Course

Are you planning a career in Data science? In this technology-driven world, it has become quite essential to have a unique set of skills that combine programming, statistics and mathematics. Data handling and analysis are important if you need to be proficient in programming languages. When you pursue a Data science course in Bhubaneswar with placement, you can learn quite a few programming languages. The knowledge can help you streamline machine learning, data cleaning and much more. Know about the top 5 programming languages that data science courses cover often.

  1. Python

Simple, flexible, and versatile, this is a user-friendly programming language. It is useful for both beginners and experts and happens to be usually the first programming language that data science courses cover. You can get an extensive library ecosystem, which includes Scikit-Learn for machine learning, NumPy for numerical computations and Pandas for data manipulation.

You can create charts and informative graphs with the use of visualization libraries like Seaborn and Matplotlib. It is a versatile language that can help you with deep learning, statistical analysis, or data processing.

  1. R

Learning this specialized language can make you an expert in data visualization and statistical analysis. For both researchers and statisticians, it can be useful. It can make you an expert in data modelling and handling complex statistical tests.

With a full set of libraries, this language allows you to perform advanced analytics, derive deep insights from complex datasets and use data for academic research.

  1. SQL (Structured Query Language)

In data science, SQL can help you manage and query relational databases easily. It might not be a regular programming language but can prove to be invaluable for you. You can use SQL to manipulate, filter and retrieve data efficiently, before making it ready to be analyzed further.

With a good knowledge of using SQL, you can easily collate data, join data tables and deal with large datasets. During Data Science Training in Bhubaneswar, you will learn SQL usage for handling challenges in any data-driven environment.

  1. Java

A robust language, Java is known to be reliable, scalable and fast. It might be regarded as useful for general purposes, but can be used in distributed computing and big data applications. It is compatible with Apache Spark, Apache Hadoop and other big data frameworks, useful for processing a large quantity of data.

It is a powerful language that allows you to deal with complex data pipelines. Naturally, it is a fixture in data science training courses focused on large-scale data processing.

  1. Julia

It is comparatively newer and can be useful for data science applications that need high efficiency and speed. Its simplicity resembles that of Python while its performance is quite close to that of languages like C++. Naturally, it is especially useful for research, finance etc. You can use its mathematical capabilities for data modelling, machine learning, and advanced analytics.

A top course at a Data Science Institute in Bhubaneswar can help you attain mastery in all these languages and more. Knowing these languages can make you a wonderful asset for any data-driven organization.