Course curriculum

    1. Segment - 01 - Installing R and R Studio

    1. Segment - 02 - Read in CSV & Excel Data

    2. Segment - 03 - Read in Unzipped Folder

    3. Segment - 04 - Read in Online CSV

    4. Segment - 05 - Read in Google Sheets

    5. Segment - 06 - Read in Data from Online HTML Tables-Part 1

    6. Segment - 07 - Read in Data from Online HTML Tables-Part 2

    7. Segment - 08 - Read Data from a Database

    1. Segment - 09 - Remove Missing Values

    2. Segment - 10 - Introduction to dplyr for Data Summarizing-Part 1

    3. Segment - 11 - Introduction to dplyr for Data Summarizing-Part 2

    4. Segment - 12 - Exploratory Data Analysis(EDA): Basic Visualizations with R

    5. Segment - 13 - More Exploratory Data Analysis with xda

    6. Segment - 14 - Data Exploration & Visualization With dplyr & ggplot2

    7. Segment - 15 - Testing for Correlation

    8. Segment - 16 - Chi Square Test

    1. Segment - 17 - How is Machine Learning Different from Statistical Data Analysis?

    2. Segment - 18 - What is Machine Learning (ML) About?

    1. Segment - 19 - K-Means Theory

    2. Segment - 20 - Other Ways of Selecting Cluster Numbers

    3. Segment - 21 - Fuzzy K-Means Clustering

    4. Segment - 22 - Weighted k-means

    5. Segment - 23 - Hierarchical Clustering in R

    6. Segment - 24 - Expectation-Maximization (EM) in R

    7. Segment - 25 - DBSCAN Clustering in R

    8. Segment - 26 - Cluster a Mixed Dataset

    9. Segment - 27 - Should We Even Do Clustering?

    1. Segment - 28 - Introduction

    2. Segment - 29 - Principal Component Analysis (PCA)

    3. Segment - 30 - More on PCA

    4. Segment - 31 - Multidimensional Scaling

    5. Segment - 32 - Singular Value Decomposition (SVD)

About this course

  • Free
  • 53 lessons
  • 6 hours of video content