Learning Python will help students develop a versatile data science toolkit, and it is a versatile programming language which can be learnt easily even as a non-programmer. On the other hand, R is a programming environment specifically designed for data analysis that is very popular in data science. The two most popular programming tools for data science work are Python and R at the moment. R for statistical analysis and Python as a general-purpose programming language.
Python for Data Science Course, will help students learn the essential concepts of Python programming and gain deep knowledge in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions.
Python is a powerful high-level, object-oriented programming language. It has wide range of applications from Web development, scientific and mathematical computing. The syntax of the language is clean and length of the code is relatively short. It allows you to think about the problem rather than focusing on the syntax. SQLite is one free lightweight database commonly used by Python programmers to store data. Many highly trafficked websites, such as YouTube, are created using Python.
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining.Data Scientists are better statistician than computer programmer and better computer programmer than the Statistician. Students who come out of school education can shape their career by intersecting in this specialization to get the huge job opportunities in the data science field. After globalization, career evangelist comes up with a new era called “Data Era”.
R is a programming language and software environment for statistical analysis, graphics representation and reporting.R is a programming language and environment commonly used in statistical computing, data analytics and scientific research.R allows us to integrate with other languages (C, C++). Thus, you can easily interact with many data sources and statistical packages. As a result, R programming language has large growing community of users.