Dates Brugg

Introductory Part

Mon, Feb 20, 2017, 12:00-16:00 Condor Introduction

Mon, Feb 27, 2017, 12:00-16:00 Coolhunting Introduction

Mon, March 6, 2017, 12:00-16:00 Statistics for Networks/Social Network Analysis

Mon, March 13, 2017, 12:00-16:00 Guest Lecture about Coolhunting by Karin Frick, GDI, virtual mirroring, ONA, Presentation e-mail network

Mon, March 20, 2017, 12:00-16:00 Facebook, Crowd Intelligence/Twitter

Mon, March 27, 2017, 12:00-16:00 KNIME/ML, Presentation Coolhunting

Mon, April 3, 2017, 12:00-16:00 Wikipedia/Behavioral Economics

Mon April 10, 2017 12:00-14:00 team formation / Mid term exam

Virtual Meeting

Mon April 10, 2017 12:00-14:00 team formation

Mon April 24, 2017 12:00-14:00 (virtual)

Mon May 8, 2017 12:00-14:00 (virtual) (project week)

Mon May 15, 2017 12:00-14:00 virtual mirror

Mon May 29, 2017 12:00-14:00 (virtual)

Mon June 12, 2017 12:00-16:00 final presentation

Local Course Info

regular class hours: Monday 12.00-16.00

school holidays: Easter Monday April 17, Pentecost Monday June 5

project week: May 8 to 12, 2017

beginning/end of term: Feb 20, 2017, June 17, 2017

course credits: 6

expected hours spent for project: 42 h (in lectures); 140 h (project work)

Local Course Info

regular class hours: Monday 12.00-16.00

school holidays: Easter Monday April 17, Pentecost Monday June 5

project week: May 8 to 12, 2017

beginning/end of term: Feb 20, 2017, June 17, 2017

course credits: 6

expected hours spent for project: 42 h (in lectures); 50 h (local project preparation), 100 h (international project work)

Project Deliverable

1. Final presentation (10-15 slide presentation, plan for 12 minutes of presentation, and 3 minutes Q&A)
   1. Goals of the project
   2. Related work (what others have done in the same area)
   3. Work process (how did you organize your work)
   4. Results
   5. Possible extensions
   6. What worked well/ what could have been done better (both from the team perspective, and for the instructors)
2. Web site (for coolhunting projects) or software/algorithms for trend prediction projects
3. Project documentation (will be the foundation for final paper written by students from Cologne/Bamberg):
   1. Coolhunting results (commented lists, network charts, plots, ...)
   2. description of own data fetchers (software used, architecture,...)
   3. repository of results
   4. insights gained

Assessment

• Virtual Mirror (15%)
• Coolhunting (15%)
• Paper presentation (10%)
• Exam (20%)
• Project (40 %)

Presentations