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    Certified Business Analytics Practitioner

    BY
    Henry Harvin

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    Mode

    Online

    Duration

    4 Days

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study, Virtual Classroom
    Mode of Delivery Video and Text Based

    Course and certificate fees

    certificate availability

    Yes

    certificate providing authority

    Henry Harvin

    The syllabus

    Module 1: Analytics

    • Analytics Definition and Applications
    • Levels of analytics
    • Quiz Module 1

    Module 2: Introduction to R programing

    • R Environment and R Studio
    • Version, R, R-studio Menu, Panes
    • Data Management
    • Enter, read, print, import/export data
    • Improving functionality with additional packages
    •  Package install, load, detach
    • Quiz Module 2

    Module 3: Data Structures & Operators

    • Data Structures
    • Operators
    • Data Types
    • Quiz Module 3

    Module 4: Data Management

    • Subsetting Data
    • Restructuring, Reorganising & Reshaping Data
    • Descriptive Statistics
    • Quiz Module 4

    Module 5: Apply Functions in R

    • Loop Family
    • Mapply, sapply, tapply
    • Quiz Module 5

    Module 6: Aggregate and Table Functions

    • Data Summarization using aggregate
    • Aggregate
    • Data Summarization using table
    • Table
    • Quiz Module 6

    Module 7: Data Manipulation In R

    • Data Summarisation using dplyr
    • dplyr package
    • Quiz Module 7

    Module 8: Graphs

    • Basic Graph intro + scatter plot
    • Basic Boxplot
    • Basic Barplot
    • Basic Histogram
    • Basic Pie-chart
    • Quiz Module 8

    Module 9: Advanced Graphs

    • Advance graph intro
    • ggplot: scatterplot
    • ggplot: barplot
    • ggplot: heatmap
    • Quiz Module 9

    Module 10: Linear Regression, Classification, and Analysis

    • Simple Linear Regression
    • Single linear regression model
    • Multi-Linear Regression
    • Multi-linear regression model
    • Logistic Regression
    • Logistic Regression Modeling: Logistic Regression Model
    • Decision Tree Classification
    • Decision Tree Classification- intro : -Decision Tree Regression - codes
    • Cluster Analysis
    • Clustering-intro: clustering models and analysis
    • Quiz Module 10

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