Data Analytics is the science of analyzing data to convert information to useful knowledge. Data mining analysis involves computer science methods at the intersection of artificial intelligence, machine learning, statistics, and database systems.
Increasingly with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses.
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.
It is easy for an individual to understand a data presented visually as compared to the data given in running text or only number form. Visual representation of data also helps in analysing and interpreting the data easily. The representation of data is called data visualisation.
R is a programming language software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. It is an approach of data analysis employed for summarizing and visualizing data set, and the focus of the approach is to analyze data’s basic structures and variables to develop a basic understanding of the data set. in this data science certification course, students will learn data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language.