MGT-644(b) / 2 credits

Teacher:

Language: English


Summary

The objective of this course is to introduce doctoral students to computational methods for data-driven empirical research in management.

Content

Keywords

Data Processing, Visualization, Cloud Computing, Data Analysis, Text Analysis, Simulation, Machine Learning. 

Assessment methods

Students will be evaluated based on five, take-home assignments – each worth 20% of the overall course grade. Each assignment should take 5 to 6 hours to complete. Each assignment is due before the start of the next class; the final assignment is due one week after the final class.

 

Create a new jupyter notebook for each assignment and commit it to your git repository. Name your jupyter notebooks sequentially as:

 

a1.ipynb   a2.ipynb   a3.ipynb   a4.ipynb   a5.ipynb

 

In the programs

  • Subject examined: Computational Methods for Doctoral Research in Management
  • Lecture: 84 Hour(s)

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22