Advanced Business Analytics with R Certificate course, Bangalore, India

Advanced Business Analytics with R Certificate course, Bangalore, India


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About The Event

Manipal Prolearn Conducting Advanced Business Analytics with R Classroom program to Get an opportunity to have a hands on experience with Excel and R and gain a competitive edge in the fast-paced world of Business Analytics.


Program Highlights:

  • Live online sessions with industry experts.
    Hands on experience with R and Excel
    Access to reading material,videos,case studies and more



  • Use various data sampling techniques to select, manipulate and analyse different data points to identify patterns and trends.
    Employees with this skill are sought after and required by small companies as well as big MNCs.
    Solve complex problems with R which is the most popular language for data science and an essential tool for Finance and analytics-driven companies.
    Gain a competitive edge in the fast-paced and competitive field of Business Analytics.
    The average pay for an Entry-Level Business Analyst, is Rs 4.8 lakhs per year in India while experienced professionals earn an average of Rs 12.6 lakhs per year.
    Hands-on experience with Excel and R, via number of Instructor Led Webinar Sessions


Course Outcome:

  • Optimise business situations that involve whole numbers, such as employees to deploy.
    Optimise business decisions that take multiple input variables to predict between two possible outputs.
    Model decisions under a variety of future uncertain states, depending on the decision maker’s proneness or aversion to risks.
    Compute correlation where, at first glance, there seem to be none – correlation between data points in a time series.
    Compute the regression model for time series data that has correlation within itself.
    Optimise business situations where two variables do not move in a linear fashion.
    Test hypothesis for experiments involving different treatments.
    Model continuous outcomes that depend on more than one input variable.
    Group data points dynamically based on the similarities among the members of each group.



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