Python Essentials for Hydrologists - On Demand Training

View More On-demand Training

About

Take sessions at any time with unlimited access for 30 days on registration.

Generative AI has made it easier than ever to produce code, but understanding Python’s core capabilities is still essential, especially for hydrologists working with spatial data, time series and large environmental datasets. This course provides clarity in a rapidly expanding ecosystem of tools and libraries.

In this 3‑part course, participants explore the Python packages that streamline everyday hydrological workflows. You will work with NumPy, Pandas and xarray for data processing, and use GeoPandas and Rasterio for geospatial analysis. The course also compares plotting libraries such as Matplotlib, Plotly, Bokeh and Seaborn, and introduces tools for building interactive dashboards to share results.

Designed for beginning to intermediate Python users, this course helps you consolidate your skills, interpret AI‑generated code with confidence and build a more efficient, modern workflow. By the end, participants will have a clear understanding of the Python landscape for hydrology and the practical know‑how to apply it to real projects.

Details

Format	3 x 2-hour sessions + course material & resources
Cost	AUD $895.00 (INC. GST)
Contact	Group Booking: For 5 or more contact us: [email protected]
Code	OD-27-3-184
Tags	Python

Register your interest: https://awschool.com.au/training/python-for-hydrologists/

Presenters

Vincent Post

Edinsi Groundwater

Vincent is a hydrogeologist with nearly 20 years of experience in Python programming. He has a strong background in academia and research and has been working as a self-employed hydrogeological consul... Read more

Onno Ebbens

Artesia

Onno Ebbens is a Dutch geohydrologist who graduated from Delft University of Technology (TU Delft) in 2015 with a degree in Water Management. His master's thesis focused on utilising time series analy... Read more

Course Overview

This course introduces the essential Python packages hydrologists rely on to process, analyse and share data. Participants will work with NumPy, Pandas and xarray for data handling, and use GeoPandas and Rasterio for geospatial analysis. The course also compares plotting tools including Matplotlib, Plotly, Bokeh and Seaborn, and shows how to build interactive dashboards for sharing results. It provides clarity on which Python tools best support real hydrological analysis and decision‑making.

Learning Outcomes

In this course, you will be able to:

Decide which Python packages are best suited for data processing and analysis needs.
Perform geospatial processing using Python tools and libraries.
Access online datasets through APIs and integrate them into hydrological workflows.
Create clear and compelling visualisations of data and model results.
Build interactive dashboards to share insights and engage stakeholders.

Course Outline

Part 1: Data Processing with Numpy, Pandas and xarray

Decide which Python packages to use for different data processing tasks.
Understand the key differences between NumPy, Pandas and xarray.
Process and store large datasets efficiently.

Part 2: Geospatial Analysis with GeoPandas and Rasterio

Understand GeoDataFrames and common geometry types.
Perform common geospatial processing tasks using GeoPandas and Rasterio.
Import and export a range of GIS file formats.

Part 3: Data Visualisation and Sharing with Matplotlib, Plotly, Bokeh and Seaborne

Choose the plotting package that best suits your workflow.
Create high‑quality graphs and figures for hydrological data.
Build interactive dashboards to share results with stakeholders.

Format

6+ hours of session recordings with unlimited access for 30-days;
Pre-and-post-course materials to go through via the AWS learning platform.
Homework exercises between the 3 parts.
Additional resources and working model download/s.
Ability to ask questions to the presenters at any time through the learning platform.

Pre-requisites

Basic knowledge of Python.
- (Optional) AWS Python Training Series course.
Understanding of fundamental GIS concepts.
- (Optional) AWS QGIS Masterclass course.

Requirements

Python installation with specific packages.
- Installation instructions will be provided via the Learning Platform.
Ability to run Jupyter notebooks (Jupyter Lab or VS Code).

Completion Certification

Participants earn CPD hours/points (i.e. with Engineers Australia) for at least 6 hours for the entire course.
On completion of the course attendees will be issued with a Certificate of Completion.

Refund Policy

Frequent Asked Questions (FAQs)