Python Training

Python for Geospatial Analysis

This is a course for scientists and researchers interested in using Python for solving computational problems and spatial analysis problems that arise in daily work.

Prerequisites

Familiarity with spatial analysis concepts is assumed. No prior experience with programming (in any language) is assumed.

Expected Outcomes

By the end of the course, you will have all the knowledge you need to start programming competently in Python. You will know what's available with Python, how to structure your code and use Python's data structures competently, and how to find further resources for learning more. You will have had experience with using Python for various scripting and scientific data manipulation tasks, with a focus on analysing spatial data.

Course Syllabus

Day 1: Introduction to Python

Day 1 covers the basics of using Python for general programming tasks, including tips and tricks for making this easy. The syllabus is as follows:

  • Why use Python? What’s possible? Python versus Java, C, C++, Matlab, R, IDL, ...
  • How to install a complete Python environment (with plotting etc.)
  • Python syntax and concepts; file IO
  • Useful data structures
  • Modularity and packaging: functions, classes, modules, packages
  • Practical tips and tricks (including rapid prototyping with the IPython shell)
  • Tour of the amazing standard library (including handling dates, CSV files, zip files)
  • Day 2: Basics of Scientific Computing with Python

    Day 2 teaches the use of Python for scientific computing. It covers array and matrix manipulation, an overview of available scientific routines, creating simple but beautiful 2D plots, and easy spreadsheet- style data analysis, with the packages NumPy, SciPy, Matplotlib, and Pandas. The syllabus is:

  • Introduction to numerical data manipulation with NumPy
  • Tour of SciPy for scientific data manipulation: optimization, statistics, sparse matrices, image denoising, classification, clustering, signal processing
  • 2D plotting with Matplotlib
  • Data analysis and modelling with Pandas (including time-series, missing values, Excel data, SQL databases)
  • Day 3: Introduction to Scripting with ArcGIS

    Day 3 dives into using Python in ArcGIS, creating and maintaining spatial analysis and geoprocessing workflows, and includes an introduction to creating scripts to work with spatial data in ArcGIS:

  • Introduction to spatial analysis in Python
  • Accessing Python from ArcGIS Desktop - the Python window and field calculations
  • Using model builder to build workflows
  • Moving from model builder to Python scripts
  • Using ArcGIS Extensions and toolboxes in Python
  • Accessing feature properties using “describe()”
  • Accessing and creating spatial objects using cursors
  • Logging and writing metadata with Python
  • Resources for finding help
  • Day 4: Open Source Handling of Spatial Data in Python

    Day 4 introduces practical open-source tools for working with spatial data. The syllabus is:

  • Reading spatial data with open-source tools: QGIS, GDAL, GRASS
  • Projections; vector analysis and the ‘shapely’ package
  • Raster image analysis in Python: worked examples with SciPy (ndimage, signal) and PIL
  • More on spatial data access using Python: introduction to accessing shape files, KML
  • Network analysis using NetworkX
  • Advanced spatial analysis topics: spatial autocorrelation with PySAL; clustering and processing large spatial datasets; future directions and overview of the ecosystem
  • Other topics

    We would happy to swap in different topics on request. Some examples are:

  • Interfacing Python with R using RPy2
  • Accessing NetCDF data
  • Code efficiency: performance measurement and optimization
  • Writing re-usable and maintainable code
  • Approaches to running large processes in Python
  • Calling an ArcGIS server task as a web service
  • Bring Your Own Data

    We also encourage you to supply your own data sets for us to use in the course if you wish.

    Supplemental materials

    We will supply you with printed course notes and a USB stick containing a complete Python environment based on VirtualBox. This saves time in the course and allows us to focus on using Python rather than installing it. The USB stick also contains kitchen-sink Python installers for multiple platforms, solutions to the programming exercises, several written tutorials, and reference documentation on Python and the third-party packages covered in the course.

    Other information

    Personal help:
    Your trainer(s) will be available after the course each day for you to ask any one-on-one questions you like — whether about the course material and exercises or about specific problems you face in your work and how to use Python to solve them.
    Food and drink:
    We will provide lunch, morning and afternoon tea, and drinks.
    Timing:
    The course will run from 9:00 to roughly 17:00 each day, with a breaks of an hour for lunch and 15 minutes each for morning and afternoon tea.

    Upcoming Courses

    Please contact us to register your interest.

    Upcoming Public Courses

    Sydney

    Python for Network Engineering:
    22 Mar – 24 Mar 2017

    View Details Book Now

    Sydney

    Python for Predictive Data Analytics:
    27 Mar – 30 Mar 2017

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    Sydney

    Introduction to Python:
    27 Mar – 28 Mar 2017

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    Canberra

    Python for Scientists & Engineers:
    08 May – 12 May 2017

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    Melbourne

    Python for Scientists & Engineers:
    10 Jul – 14 Jul 2017

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    Sydney

    Python for Scientists & Engineers:
    14 Aug – 18 Aug 2017

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    Location

    Testimonials

    “One of the best programming courses I have attended - thanks!”

    - Giant Billen, IAG Insurance

    “Excellent training course, excellently presented. Perhaps the best that I have had in the area of IT / programming.”

    - George Grozev, CSIRO (Clayton)

    “Both Ed and Henry presented well…. The course structure was adjusted to suit the participants quickly and easily.”

    - Jenet Austin, CSIRO (Black Mountain Laboratory)

    “Course content was well presented and easily digested. Practical exercises were an essential part of the course – a good ratio of lecture/play was achieved. Well done Ed and Henry!”

    - Steve Zegelin, CSIRO (Black Mountain Laboratory)

    “Very comprehensive intro to every aspect of python. Highly qualified trainer. Beyond my expectation on every aspect. ”

    - Baichuan Sun, CSIRO (Clayton)

    “I loved it. Ed was inspiring.”

    - Onoriode Coast, CSIRO (Narrabri, NSW)

    “One of the best training courses I've been on.”

    - David Scurrah, Bureau of Meteorology (Melbourne)

    “Instructor was superb - very impressive. I really enjoyed the course - thanks!”

    - Steven Edgar, CSIRO (Hobart)

    “Simply awesome!!”

    - James Park, Cisco (St Leonards)

    “It was a pleasure ... Shared feedback from all involved was that it’s been one of the most beneficial and well delivered training courses we’ve been a part of.”

    - Dylan Matthews, Simply Energy / GDF Suez (Melbourne)

    “Very impressed with the course, delivery. And depth of knowledge of Ed and Henry. Far exceeded my expectations and has greatly improved my core skills as well as inspired so many new ideas for my current work / projects. Thank you!”

    - Kelsey Druken, National Computational Infrastructure (Canberra)

    “The course was delivered by trainers who were extremely knowledgeable in their field. It was really good to learn from the best!”

    - Marius Roman, Transurban (Melbourne)

    “Really impressed by Python's capability and excited to use as alternative to MatLab, as is free and better supported.”

    - Carsten Hofmann, OMC International (Melbourne)

    “Was the most fulfilling and rewarding class I have taken since "general relativity" at uni. Was extremely well run. Excellent all round!”

    - Dr Millicent Maier, Australian Astronomical Observatory (Sydney)

    “This course has shown me how I could have done the work I was doing just last week 10x more efficiently in Python.”

    - Maruf Rahman, Geoscience Australia (Canberra)

    “The VM setup and USB is great. Ed is an excellent instructor - he presents well and welcomes any questions. He is clearly a super smart guy who has a great grasp on what he is teaching - able to just prototype on the fly and the course overall really opened my eyes to python. ”

    - Jack Hendy, Optiver (Sydney)

    “Great course. Enjoyed it and will follow up with some practical implementation of some of the work.”

    - Adam Grace, Optus (Sydney)