Introduction to Python GIS- CSC Training 2018

Key Info
URL - the landing page for the learning resource: 
https://automating-gis-processes.github.io/CSC18/index.html
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

Introduction to Python GIS is 6 lessons organized by CSC Finland – IT Center for Science. During the course you will learn how to do different GIS-related tasks in Python programming language. Each lesson is a tutorial with specific topic(s) + Exercises where the aim is to learn how to solve common GIS-related problems and tasks using Python tools. Lecturer of the course is Henrikki Tenkanen who is a geo-data scientist and postdoctoral researcher at the Digital Geography Lab, University of Helsinki. These lessons are for  those who know the basics of Python programming.  If Python is not familiar to you, we recommend to start with a course from us focusing on the basics of Python from geo-python.github.io.

The majority of this course will be spent in front of a computer learning to program in the Python language and working on exercises. The provided exercises will focus on developing basic programming skills using the Python language and applying those skills to various GIS related problems.

Learning objectives

At the end of the course you should have a basic idea how to conduct following GIS tasks in Python:

Read / write spatial data from/to different file formats
Deal with different projections
Conduct different geometric operations and spatial queries
Convert addresses to points (+ vice versa) i.e. do geocoding
Reclassify your data based on different criteria
Know how to fetch data from OpenStreetMap easily with Python
Know the basics of raster processing in Python
Visualize data and create (interactive) maps

Course information

Lesson 1:GIS with Python; Spatial data model; Geometric Objects; Shapely
Lesson 2:Working with Geo Data Frames; Managing projections
Lesson 3: Geocoding; Table join; Working with Open Street Map data
Lesson 4: Geometric operations; Spatial queries
Lesson 5: Visualization, making static and interactive maps
Lesson 6:Raster processing in Python

Authoring Person(s) Name: 
Henrikki Tenkanen
Authoring Organization(s) Name: 
CSC Finland – IT Center for Science
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution 4.0 International - CC BY 4.0
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
English
More info about
Keywords - short phrases describing what the learning resource is about: 
Data analysis
Data visualization
Geographic Information System (GIS)
Python
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Physical Sciences and Mathematics: Earth Sciences
Physical Sciences and Mathematics: Environmental Sciences
Published / Broadcast: 
Thursday, January 18, 2018
Publisher - organization credited with publishing or broadcasting the learning resource: 
University of Helsinki
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Interactive Resource - requires a user to take action or make a request in order for the content to be understood, executed or experienced.
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management or data skills.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Course - series of units and lessons used to teach the skills and knowledge required by its curriculum.
Target Audience - intended audience for which the learning resource was created: 
Data policymaker
Data professional
Early-career research scientist
Graduate student
Mid-career research scientist
Software engineer
Technology expert group
Undergraduate student
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 Day (but less than 1 week)