SURV642: Project Consulting Course

Area: 
Data Analysis
Credit(s)/ECTS: 
6/12
Core/Elective: 
Elective

This course focuses on the process of finding and extracting useful information and insights from data using survey and data science methods. At the beginning of the course, students will be introduced to a number of clients (organizations or companies) who will present particular problems/research questions that they would like to address using data. Students will be split into groups and will have an opportunity to choose a problem to work on. The real-world context of the course will help students to learn to balance high-quality work, effective collaboration, and planning as well as time management. While there will be some lecture and reading material, the main resource of the course will entail a close interaction with other students and the course instructor. By the middle of the course, students will be asked to make a 5-minute online presentation reporting on their progress. At the end of the course, students are expected to present their results and submit a written report. In addition to participating in regular online meetings attended by all of the students, team are expected to meet on a regular basis (Zoom virtual rooms will be provided).

Course objectives: 

By the end of the course, students will…

  • apply skills and concepts learned throughout the program to solve a real-world problem for a given client
  • learn how to successfully manage a project in a timely manger
  • learn how to collaborate with team members as well as data clients
  • learn how to effectively communicate results in both written and oral forms
Grading: 

Grading will be based on

  • participation in bi-weekly online meetings (10%)
  • mid-term progress presentation (20%)
  • final presentation (35%)
  • final report (35%)
Prerequisites: 
  • successful completion of the course “Fundamentals of Survey and Data Science”
  • experience with descriptive statistics, inferential statistics and linear modeling
  • familiarity with R or Python (you should be able to clean and manipulate data using one of these programing languages)

Course Dates

2018

Fall Term (September – November)