Class Details
GIS Course: Introduction
Course summary
In the digital age, understanding spatial data is critical in making informed business decisions. Generating insights from location data requires special tools – Geographic Information Systems (GIS). By combining spatial information, computer technology, and geography, GIS enables analysts, managers, and researchers to create intuitive knowledge capturing the spatial dimension.
This GIS introductory course will show you fundamental Geographic Information Systems skills. Learning GIS will take place using “industry standard” software suite ESRI ArcGIS Pro and will also introduce its free, open-source alternative QGIS. You will learn spatial data types, prepare ArcMap documents, import/export spatial data, apply geoprocessing tools and create beautiful maps.
By the end of the course, you will have solid mapping and spatial analytics skills. Regardless of your skill level, you will gain a newfound confidence using ArcGIS Pro and QGIS.
Aims
This course aims to provide a hands-on introduction to Geographic Information Systems (GIS) using industry-standard software, ESRI ArcGIS Pro. We want to empower you to confidently work with spatial data and GIS software.
Learning outcomes
By the end of this course, you should be able to:
- describe what a Geographic Information System (GIS) is
- operate ArcGIS Pro software packages
- work with spatial data
- differential between .shp, .gdb, and raster files
- make beautiful and informative maps
- geoprocess spatial data
- find, download, and use ABS statistical geography.
Content
- Geographic Information Systems
- ESRI ArcGIS Pro software
- Brief overview of QGIS
- Types of spatial data – vector and raster
- File types - .shp vs geodatabase
- Coordinate systems
- Geoprocessing and spatial data manipulation techniques
- Creating maps using principles of cartography
Who this course is for
Analysts, business professionals, managers, IT knowledge workers and lifelong learners looking to master spatial data will find this course advantageous.
Prerequisites
While no programming is required for this class, some basic proficiency working with data is required.
Delivery style
Taught over one day, through a series of concepts, examples, problem exercises, and in-class knowledge challenges. The material is presented so that participants of varying backgrounds, skills and abilities can all move together in a brisk but comfortable learning pace.
Utilising principles of productivity, efficiency, and time management, the course material and timeline is structured to optimise learning.
Delivery mode
Face-to-face, presenter-taught training in a computer lab. You will be provided with ArcGIS Pro software login details for the day of the course.
Materials
All course materials and files are available electronically (via Dropbox).
Sessions
Location
Face-to-face (CCE Building, Sydney)
Public transport
As bus and train timetables regularly change, we suggest you visit the Transport for NSW trip planner before you set out.
The nearest train stations are Newtown Station and Macdonaldtown Station. Macdonaldtown Station is closer by distance than Newtown Station, however trains do not stop as frequently as at Newtown Station.
Other information
Parking
Nearby parking is available at Wilson Parking - RPA Medical Centre Car Park (entry via Elizabeth Street off Carillon Avenue).
A Flexi Saver Rate is available but must be booked in advance online and includes the booking fee. Bookings can be made via the Wilson website or by downloading the Wilson Parking App. Otherwise, hourly parking rates will apply, as advertised on the Wilson Parking website.
Meet the facilitators
Paul Yacobellis
Paul Yacobellis has been helping professionals optimise their personal productivity for the past 10 years. He has assisted management and individuals implement time saving, energy maximising techniques. He has lead training sessions that cut out wasteful time, reduce stress, and increase overall well-being. Paul’s techniques range from technical to behavioural.
Paul also has experience in data mining and big data analytics, statistical computing, economic/econometric consulting, spatial statistics and Geographic Information Systems (GIS), transport modelling, and business development. He has consulted with government agencies, private corporations and universities, and has previously taught statistics, mathematics, economics and computer science at the University of Central Florida, Orlando.
Paul holds a Master’s in Statistical Computing (Data Mining track) and a Bachelor of Science in Economics and Mathematics.
When not sharing his passion for enhanced personal productivity, Paul works fulltime as data scientist and enjoys parenthood, long-distance running and reading great books.
