For six weeks this summer, students have worked on various data science-related cases provided by five different work-life organizations. On Thursday the 4th of August, they will present their findings to an open audience at the auditorium in Statistics Norway.
Where? Akersveien 26 (Statistics Norway), the Auditorium.
Or digitally: Political Data Science Hackathon presentasjoner - YouTube
When? Thursday 4th of August from 10:00-15:30
How? Please give us an indication here if you'd like to join in the audience.
|
Event |
Time |
|
Introduction by course holders |
10:00-10:15 |
|
Introduction by ISS |
10:15-10:30 |
|
First presentation: Statistics Norway |
10:30-11:00 |
|
Second presentation: The Office of the Auditor General of Norway (OAG) |
11:00-11:30 |
|
Lunch in the SSB cafeteria |
11:30-12:30 |
|
Third presentation: OPX |
12:30-13:00 |
|
Fourth presentation: NORAD |
13:00-13:30 |
|
Fifth presentation: United Nations Association of Norway (UNA) |
13:30-14:00 |
|
Deliberation in the jury |
14:00-14:30 |
|
Announcement of 1-UP awards |
14:30-14:45 |
|
Announcement of winners |
14:45-15:00 |
|
Conclusion and mingling |
15:00-15:30 |
|
PODS Celebration at Vulkan Mathallen |
15:30-17:00 |
What is ISSSV1337?
The Political Data Science Hackathon course (ISSSV1337) was made by Alex Moltzau, Sondre Elstad and Solveig Bjørkholt. With help and inspiration from people in the PODS group, we were able to construct a course that is trying out a new way of learning. Thanks to the International Summer School at UiO, we were able to pilot our idea. What is the idea? Well...
- Students work in groups with a pass/fail grade to motivate collaboration and peer learning.
- The groups develop solutions for work-life relevant cases provided by different organizations, which touch upon how one could use data for social purposes.
- The organizations join us in the final presentations to decide on a winner team.
- During the course, we lecture a bit on data science related concepts (general programming, databases, APIs, webscraping, text handling, machine learning), but we also utilize workshop hours, which allow students to learn from each other and ask questions related to their cases.
Feel free to join parts or the whole event, we'd love to see you there!