Business Analytics with R Training

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Business Analytics with R Course Overview

Business Analytics with R Training Curriculum Introduction To Business Analytics Understand Business Analytics and R, Knowledge on the R language community and ecosystem, Understand the use of ‘R’ in the industry, Compare R with other software in analytics, Install R and the packages useful for the course, Perform basic operations in R using command line, Learn the use of IDE R, Studio and Various GUI, Use the ‘R help’ feature in R, Knowledge about the worldwide R community collaboration. Introduction To R Programming The various kinds of data types in R and its appropriate uses, The built-in functions in R like: seq(), cbind (), rbind(), merge(), Knowledge on the various Sub-setting methods in R, Summarize data by using functions like: str(), class(), length(), nrow(), ncol() in R, Use of functions like head(), tail() for inspecting data, Indulge in a class activity to summarize data in R Data Manipulation In R The various steps involved in R for Data Cleaning, Functions used in R for Data Inspection, Tackling the problems faced during Data Cleaning, Uses of the functions like grep(),sub(), Coerce the data in R, Uses of the apply() functions. Data Import Techniques In R Import data from spreadsheets and text files into R, Import data from other statistical formats like sas7bdat and spss into R, Packages installation used for database import, Connect to RDBMS from R using ODBC and basic SQL queries in R, Basics of Web Scraping in R R Exploratory Data Analysis Understanding the Exploratory Data Analysis(EDA), Implementation of EDA on various datasets in R, Box plots, Understanding the cor() in R, EDA functions like summarize(), llist(), Multiple packages in R for data analysis, The Fancy plots like Segment plot and HC plot in R. Data Visualization In R Understanding on Data Visualization, Graphical functions present in R, Plot various graphs in R like table plot,histogram,box plot, Customizing Graphical Parameters to improvise the plots, Understanding GUIs like Deducer and R Commander, Introduction to Spatial Analysis in R Data Mining: Clustering Techniques Introduction to Data Mining in R, Understanding Machine Learning, Supervised and, Unsupervised Machine Learning Algorithms in R, K-means Clustering. Data Mining: Association Rule Mining And Sentiment Analysis Association Rule Mining in R, Sentiment Analysis. Linear And Logistic Regression In R Linear Regression in R, Logistic Regression in R Anova And Predictive Analysis In R Anova, Predictive Analysis. R Data Mining: Decision Trees And Random Forest Decision Trees in R, Algorithm for creating Decision Trees, Greedy Approach: Entropy and Information Gain, Creating a Perfect Decision Tree in R, R Classification Rules for Decision Trees, Concepts of Random Forest in R, Working of Random Forest in R, Features of Random Forest in R Project Analyse Census Data, To predict insights on the income of the people, Based on the factors like : Age, education, work-class, occupation, etc. Salary Trends Average Business Analytics With R Salary in USA is increasing and is much better than other products. Ref: Indeed.com
Course Duration 30 hrs
Live Projects 2
Next Batch 15 Dec, 2019
19 Dec, 2019
22 Dec, 2019

Business Analytics with R Course Curriculum

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