gl2668 / r_for_data_science

Slides, Practice Assignments and Datasets. Please refer to the README for quick links to the course materials!

R for Data Science

This is the github repository for a short introductory course to R and how to use R for data science.

The slides and content are a consolidation of lessons and courses that I have picked up during my graduate studies at Columbia University.

Course Content

Slides:

• Class 1 - Introduction
• Class 2 - Data Wrangling
• Class 2 - Data Visualisation
• Class 3 - EDA & Missing Data
• Class 4 - Functional Programming

Practice Assignments:

• Assignment 1
• Assignment 2

Datasets:

• Cleveland Heart Disease dataset taken from UC Irvine

Course Outline:

• Class 1
  • Basic R Programming
  • Importing and Writing Data
• Class 2
  • Data wrangling and manipulation with dplyr
  • Data visualization with ggplot2
• Class 3
  • Exploratory Data Analysis
  • Dealing with Missing Data using naniar
  • Work on Assignment 1 together
• Class 4
  • Functional Programming
• Class 5
  • Basic Regression Analysis
• Class 6
  • Basic Machine Learning Concepts with caret
• Class 7
  • Working with strings using stringr and rebus packages
  • Simple NLP using tidytext, tm and wordcloud
• Class 8
  • Webscrapping with rvest
  • API with httr
• Class 9
  • Dashboard & Website Building with shiny

Shoutout to raw.githack for making the viewing of raw html slides possible