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Course Outline
Introduction to GIS
Installation and Required Packages
Introduction to Shapely for Geometric Objects
Intro to Pandas and GeoPandas
Managing maps and Projections
Geocoding and ArcGIS API
Geocoding Point in Polygons with GeoPandas
Spatial join
Data Classification; pysal map classifier
Overlay Analysis
Aggregating spatial data
Geometries simplifications
Visualization with Bokeh
Static and Interactive Maps
Using GIS Applications
ArcGIS API usage and processing toolbox
Python in QGIS; Processing toolbox & graphical modeller
Creating own processing toolbox;
Network Analysis and OpenStreetMap
Downloading and working with OpenStreetMap data; Osmnx
Network analysis in Python; Networkx; Osmnx;
Conclusion
Requirements
A prior experience with Python for Machine Learning and with the libraries like pandas, matplotlib is highly recommended.
21 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (2)
I'm looking forward to having a training again with Any, he was really good, I'm just a GIS guy, but Any made everything clear to me, he explained complex processes in layman's terms. Keep it up, thank you.
Lwazi Qhingana - South African National Roads Agency (SANRAL) SOC Ltd
Course - Python for Geographic Information System (GIS)
I really enjoyed the training. I found all modules to be applicable to problems that I am trying to solve at work. The integration of the training with jupyter notebooks was really impressive.
