Course curriculum

    1. How to use the course's web interface (there is no other video for this course)

    2. About The Course

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    3. About The Author

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    4. Table of Contents

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    1. Chapter 1: From Instinct to Insight

    2. R SkillBox 1: Installing R/RStudio and Understanding RStudio Interface

    3. Chapter 2: Data as the Ingredients of Decision Making: Organizing Data for Accessibility and Analysis

    4. R SkillBox 2: Importing and Exporting Data in R (CSV and Excel)

    5. Chapter 3. Analytics as the Refining Fire for Decision Making: Analyzing Data for Insights

    6. R Skillbox 3: Exploring and Transforming Data Using str(), as.*(), and summary.

    1. Chapter 4: Mapping the Analytics Toolbox

    2. R SkillBox 4: Working with Packages and Libraries

    3. Chapter 5. Getting Started with R and RStudio

    4. R SkillBox 5: Creating and Managing Scripts (R code)

    5. Chapter 6. Understanding Data Objects and Structures in R

    6. R Skillbox 6: Creating, Inspecting, and Managing Objects in R

    1. Chapter 7: Data Mining in Context — History, Practice, and Project Launch

    2. R SkillBox 7: Cleaning and Preparing Data with dplyr and tidyr

    3. Chapter 8. Techniques That Matter: From Classification to Prediction to Clustering

    4. R Skillbox 8 — Experiencing 4-Means Clustering with mtcars

    5. Chapter 9. Exploratory Data Analysis in R — Summarizing Data

    6. R Skillbox 9: From Summaries to KPIs to BI (with EDA)

    7. Chapter 10. Data Visualizations for EDA and BI

    8. R Skillbox 10: Creating Dashboards with ggplot2, patchwork, and Shiny

    9. Chapter 11. Mining Data for Predictions

    10. R Skillbox 11: Predictive Modeling in Action

    11. Chapter 12. Mine Data for Direct and Indirect Root Causes

    12. R Skillbox 12: Stepwise Predictor Selection with lm() and step()

    13. Chapter 13. Beyond One Cause: Modeling Interacting Influences in Predictive Analytics

    14. R Skillbox 13: Quantifying Joint Causation with Multiple Regression

    15. Chapter 14. Chapter 14 A Best Practice in Predictive Analytics: KPIs for Predictive Analytics

    16. R Skillbox 14: Cross-Validation with caret and confusionMatrix()

    17. Chapter 15. From Insight to Influence — Communicating Analytics for Action

    18. R Skillbox 15: Turning Analysis into Story

About this course

  • 15 exploration lessons
  • 15 experiential exercises
  • 2 business cases

Discover potentials, Starting today

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