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  • 1 - 1 - Series Motivation (12-03).srt
  • 1 - 10 - Regression Models Overview (1-46).srt
  • 1 - 11 - Practical Machine Learning Overview (1-31).srt
  • 1 - 12 - Building Data Products Overview (1-19).srt
  • 1 - 13 - Installing R on Windows (3-20) {Roger Peng}.srt
  • 1 - 14 - Install R on a Mac (2-02) {Roger Peng}.srt
  • 1 - 15 - Installing Rstudio (1-36) {Roger Peng}.srt
  • 1 - 2 - The Data Scientist-'s Toolbox (5-09).srt
  • 1 - 3 - Getting Help (8-52).srt
  • 1 - 4 - Finding Answers (4-35).srt
  • 1 - 5 - R Programming Overview (2-12).srt
  • 1 - 6 - Getting Data Overview (1-34).srt
  • 1 - 7 - Exploratory Data Analysis Overview (1-21).srt
  • 1 - 8 - Reproducible Research Overview (1-27).srt
  • 1 - 9 - Statistical Inference Overview (1-06).srt
  • 2 - 2 - Command Line Interface (16-04).srt
  • 2 - 3 - Introduction to Git (4-49).srt
  • 2 - 4 - Introduction to Github (3-53).srt
  • 2 - 5 - Creating a Github Repository (5-51).srt
  • 2 - 6 - Basic Git Commands (5-52).srt
  • 2 - 7 - Basic Markdown (2-22).srt
  • 2 - 8 - Installing R Packages (5-37).srt
  • 2 - 9 - Installing Rtools (2-29).srt
  • 3 - 1 - Types of Questions (9-09).srt
  • 3 - 2 - What is Data- (5-15).srt
  • 3 - 3 - What About Big Data- (4-15).srt
  • 3 - 4 - Experimental Design (15-59).srt
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