Exploratory data analysis is an approach for summarizing and visualizing the important characteristics of a data set. Exploratory data analysis focuses on exploring data to understand the data’s underlying structure and variables, to develop intuition about the data set, to consider how that data set came into existence, and to decide how it can be investigated with more formal statistical methods. R is a programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.
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.
1. Learn Data Science with R in real world, Project Life cycle, and Data Acquisition & Understand Machine Learning Algorithms & Study the tools and techniques of Experimentation, Evaluation and Project Deployment
2. Learn the concept of Prediction and Analysis Segmentation through Clustering & Learn the basics of Big Data and ways to integrate R
3. Explore data at multiple levels using appropriate visualizations & Acquire statistical knowledge for summarizing data
4. Demonstrate curiosity and skepticism when performing data analysis & Develop intuition around a data set and understand how the data was generated.
There are no particular prerequisites for this Training Course. If you love mathematics, it is helpful to learn Data Science.