DATA 133: Introduction to Data Science I -- Resources (fall2020)

Lecture slides:

• Day 1: Introduction

• Day 2: Introduction of data science and R environment

• Day 3: R vector and list

• Day 4: R Matrices, Factor and subsetting

• Day 5: R read and write to file

• Day 6: Control structure in R

• Day 7: Function in R

• Day 8: Review function in R
  

• Day 9: R plot
  

• Day 10: R debugging
  

• Day 14: Introduction to Python I
  

• Day 15: Introduction to Python II
  

• Day 16: Introduction to Python III
  

• Day 17: Introduction to Python VI
  

• Day 18: Get data
  

• Day 19: Visualizing data
  

• Day 20: Linear Algebra and Statistics
  

• Day 21: Probability
  

• Day 22: Twitter API and Invited talk
  

• Day 23: More Twitter API
  

• Day 24: Machine Learning
  

Class Materials:

• Account Requests via the CS HUB

Other useful software:

• Rstudio, great R IDE
• Atom editor
• FileZilla, PuTTY, OpenSSH and WinSCP Clients via the HUB (tools and instructions for accessing your files on the CS server).
• Eclipse (free, full featured Python IDE)