Spring school: Data Science methods within Geoinformatics

Date: April, 24 - 26, 2019, Venue: Techno_Z

Preliminary programme:

If you would like to participate please register here.

Wednesday, 24 April
10:00 – 10:30  GI-lecture Welcome, organizational issues Thomas Blaschke & Bernd Resch
10:30 – 12:00  GI-lecture Overview lecture: AI – Machine Learning – Deep Learning Pavlos Kazakopoulos
13:00 -  14:30 
15:00 – 16:30
 GI-lab Tutorial: Machine Learning with Tensor Flow (not mandatory) Omid Ghorbanzadeh & Alessandro Crivellari
16:45 – 17:45  IDEAS::lab Aftermaths: food for thought and for the body all
Thursday 25 April
9:00 – 9:15  GI-lecture Setting the scene Thomas Blaschke & Bernd Resch
9:15– 10:15  GI-lecture geoAI: "Intelligent" Geospatial Analysis: Machine Learning on Geospatial Data  

Bernd Resch & Clemens Havas & Jakob Miksch
10:45– 12:45  GI-lab geoAI: Machine learning for Multi-dimensional Social Media Analysis
14:00 – 15:00  GI-lecture Bayes 2.0 Stefan Wegenkittl
15:15 – 16:15  GI-lab Hands-on session Pavlos Kazakopoulos
16:30 – 18:00  IDEAS::lab Bar camp and market place: write ad-hoc contributions on a whiteboard – we rely on participants’ passion! all
18:00 - ……  outside The social side of Geoinformatics and Data Science  
Friday 26 April
9:00 – 9:30  GI-lecture EO big data lecture
Dirk Tiede & Martin Sudmanns
9:30 – 11:00  GI-lab lab session with Google Earth Engine (GEE)
11.15 - 12:15 GI-lecture Outlook and discussion: beyond GEE all
13:00 – 13:20  GI-lecture Text mining and deep learning: an application in economics and innovation research Jan Kinne
13:20 – 15:00  GI-lab Hands-on experience („live Coding); python modules scikit learn & Keras (TensorFlow based) for Machine Learning/Neuronal Networks Jan Kinne
15:00 – 16:00  GI-lecture Final discussion, conclusions, future actions all