R and Python are both open-source programming languages with a large community. New libraries or tools are added continuously to their respective catalog. R is mainly used for statistical analysis while Python provides a more general approach to data science.
DurationR and Python are both open-source programming languages with a large community. New libraries or tools are added continuously to their respective catalog. R is mainly used for statistical analysis while Python provides a more general approach to data science.
R and Python are state of the art in terms of programming language oriented towards data science. Learning both of them is, of course, the ideal solution. Python is a general-purpose language with a readable syntax.
R, however, is built by statisticians and encompasses their specific language. R has now one of the richest ecosystems to perform data analysis. The rich variety of library makes R the first choice for statistical analysis, especially for specialized analytical work.
Python is a tool to deploy and implement machine learning at a large-scale. Python codes are easier to maintain and more robust than R. Years ago; Python didn't have many data analysis and machine learning libraries. Recently, Python is catching up and provides cutting-edge API for machine learning or Artificial Intelligence.
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Our Mission:
To offer advanced education to students through comprehensive and job-oriented academic courses with enhanced technology, resolute interdisciplinary loom with comprehensive reach, state-of-the-art research intellects, scholarly quest, and pertinent industry involvement.
Our Vision:
Our vision is that Clinlogics will be the natural choice for superior skilled education and , innovative learning. Clinlogics will be an indispensable contributor to high quality education that meet the needs of the current industry.
We will demonstrate rigorous, technology obsessed and interdisciplinary approach to education for imminent professionals in diverse industries. We visualize Clinlogics as an abode in the academic world where training and Industry needs converge closer for reciprocal and constructive benefits.
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