Course schedule#
Week |
Data type |
Lecture |
Tutorial #1 |
Tutorial #2 |
Grading |
|---|---|---|---|---|---|
1 |
Course Introduction |
Introduction to Python |
Introduction to Data Analysis |
pass/fail |
|
2 |
Census data |
Introduction to Random Forests |
Data Exploration & Regression |
Random Forests |
12% of grade |
3 |
Census data |
Introduction to Neural Networks |
Neural Networks |
Model Validation |
12% of grade |
4 |
Satellite data |
Earth Observation & Google Earth Engine |
Land-use classification |
Drought detection |
12% of grade |
5 |
Open-Source and VGI data |
Big Data in the public domain |
Working with OpenStreetMap |
Natural Hazard Risk Assessment |
12% of grade |
6 |
Social media data |
Social Media and Natural Language Processing (NLP) |
Social Media & Natural Hazards |
Social Media & Valuation of Landscapes |
12% of grade |
7 |
How to: Visualization |
Visualizing your results |
pass/fail |
||
8 |
Exam (40%) |