MGMT4966/MGMT6560 Spring 2018
- Contact Info
- Office/Lab Hours
- Schedule
  - Session 1
  - Session 2
  - Session 3
  - Session 4
  - Session 5
  - Session 6
  - Session 7
  - Session 8
  - Session 9
  - Session 10
  - Session 11
  - Session 12
  - Session 13
  - Session 14
  - Session 15 (midterm)
  - Session 16
  - Session 17
  - Session 18
  - Session 19
  - Session 20
  - Session 21
  - Session 22
  - Session 23
- Assignments
- Grading
- Project
MGMT6560 Fall 2018
- Contact Info
- Office/Lab Hours
- Schedule
  - Session 1
  - Session 2
  - Session 3
  - Session 4
  - Session 5
  - Session 6
  - Session 7
  - Session 8
  - Session 9
  - Session 10
  - Session 11
  - Session 12
  - Session 13
  - Session 14
  - Session 15 (midterm)
  - Session 16
  - Session 17
  - Session 19
  - Session 20
  - Session 21
  - Session 22
  - Session 23
  - Session 24
  - Session 25
  - Session 26
- Assignments
- Grading
- Project
MGMT6560 Spring 2019
- Contact Info
- Office/Lab Hours
- Schedule
  - Session 1
  - Session 2
  - Session 3
  - Session 4
  - Session 5
  - Session 6
  - Session 7
  - Session 8
  - Session 9
  - Session 10
  - Session 11
  - Session 12
  - Session 13
  - Session 14 (midterm)
  - Session 15
  - Session 16
  - Session 17
  - Session 18
  - Session 19
  - Session 20
  - Session 21
  - Session 22
  - Session 23
  - Session 24
  - All Notebooks
- Assignments
- Grading
- Project
mgmt6560-fa17-Tech Fundamentals
- Contact Info
- Office/Lab Hours
- Schedule
  - Class 1
  - Class 2
  - Class 3
  - Class 4
  - Class 5
  - Class 6
  - Class 7
  - Class 8 - Midterm
  - Class 9
  - Class 10
  - Class 11
  - Class 12
  - Class 13
  - Class 14
  - Final
- Grading
- Assignments
- Project 1
- Project 2
Compute Environment
- Git/GitHub
- Anaconda
Additional Resources
- Online Classes
- Podcasts
- Git
- Python
- R
- Books
Proposals

Important Links

Course Materials

Jupyterhub

LMS

Join Slack (rpi email)

Dropbox Share

Course Website

RPI Analytics Dojo > Additional Resources > R

R

Introduction to Statistical Learning (Free online PDF)
R for Data Science (available online)
Berkeley R Bootcamp