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Data analysis is the upcoming domain offering huge opportunities. Data analysis is focused on analyzing data sets, applying statistical and analytical techniques for decision making and prediction for business success.
R is a open source programming language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, etc) and graphical techniques, and is highly extensible.
R is extensively used for statistical computations, data analysis and graphical representation of data. Candidates with certification in Data analysis with R, can tap into massive opportunities of employment and career progression.
* Hard copy material is not applicable for this course.
The certification is suitable for programmers, software developers, senior and executive management wanting to excel in data analysis. It is also well suited for those who are already working and would like to take certification for further career progression in data analytics.
Earning Vskills Data Analysis with R Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.
Job seekers looking to find employment in IT or software development or analysis departments of various companies, role in decision making, performance improvement and optimization in MNCs, corporate, senior management role. Students who want to learn Data Analysis with R and get recognition of their data analysis skills using R programming language should also take this certification.
Job seekers looking to find employment in various companies IT companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.
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Tags: Data analysis,
Descriptive Statistical Measures,
Sampling and Estimation,
R Programming Language Introduction,
Reading Data from files,
Statistical Models in R,
R Graphics Facilities,
R Data Import/Export